WPS8725


Policy Research Working Paper                        8725




        Inequality of Access to Opportunities
            and Socioeconomic Mobility
           Evidence from the Life in Transition Survey

                                Alexandru Cojocaru




Poverty and Equity Global Practice
February 2019
Policy Research Working Paper 8725


  Abstract
  Expectations of future socioeconomic mobility are an                               and (ii) when informal connections are unavailable, it mat-
  important determinant of cur- rent policy preferences. But                         ters for your aspirations whether you perceive connections
  how may these expectations be formed? Using Life in Tran-                          to be vital or not. There is also some evidence that in the
  sition survey data for a large set of transition economies and                     European Union, where formal institutions are stronger,
  several Western European countries, this paper examines                            individuals are less likely to resort to informal institutions
  the link between beliefs about the importance of personal                          such as personal connections, even when these are avail-
  connections for getting access to opportunities, such as a                         able. Perceptions of unequal access to opportunities are
  good job or university education, and expectations of future                       also linked with stronger redistributive preferences. Finally,
  socioeconomic mobility. The analysis of survey data finds                          there is some evidence that unequal access to opportunities
  evidence that: (i) lack of connections is associated with                          is associated not only with lower intragenerational mobility,
  expectations of a lower position on the future social ladder;                      but also with lower intergenerational mobility.




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 open access to its research and make a contribution to development policy discussions around the world. Policy Research
 Working Papers are also posted on the Web at http://www.worldbank.org/research. The author may be contacted at
 acojocaru@worldbank.org.




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   Inequality of Access to Opportunities and Socio-economic
     Mobility: Evidence from the Life in Transition Survey

                               Alexandru Cojocaru




Keywords: social mobility, inequality of opportunity, transition economies.
JEL Codes : D3, I32, P20.
1. Introduction

   Does one need connections to get ahead in life? Three-quarters of adults, accord-
ing to the data from the latest round of the Life in Transition Survey that queries
adults across all transition economies and several Western European countries on
their attitudes toward many aspects of life, report that connections are at least mod-
erately important (more than half think them very important or essential) to get a
good job in the government sector. More than two-thirds think connections are at
least moderately important to get a good job in the private sector (EBRD, 2017).
If socio-economic mobility is a universal human aspiration, of parents hoping for a
better life for their children, as argued in the recent World Bank report Fair Progress?
Economic Mobility Across Generations Around the World (Narayan, Van der Weide
et al., 2018), then these subjective assessments, based on nationally representative
data covering a region with a population of about 500 million adults, present a very
bleak picture of the perceived equality of opportunity for success in life.
   A related, but different question is whether the perceived need for (and availability
of) connections to access opportunities affects one’s expectations of future mobility?
In other words, if chances for success are not equal, then the extent of one’s future
mobility may be a function of access to connections or other factors that facilitate
mobility. However, perceptions of inequality may influence not only where one ends
up in the future, but also one’s own belief of where he or she will end up in the future,
that is, one’s expectations of (or aspirations for) future mobility. The importance of
the link between inequality (and inequality of opportunity) on one hand and mobility
on the other, is illustrated prominently by the The Great Gatsby Curve (Corak, 2017)
which shows high levels of inequality to be associated with low levels of experienced
mobility. The link between inequality and expectations of mobility is important in
its own right because (i) expectations of mobility may affect investments in human
capital for self and children, which will then affect actual mobility (Hoff, 2012; Geni-
cot and Ray, 2017); and because (ii) expectations of future mobility are important
determinants of current policy preferences, in particular with respect to redistribution
(Benabou and Ok, 2001; Ravallion and Lokshin, 2000; Checchi and Filippin, 2004;

                                           2
Alesina and La Ferrara, 2005; Alesina and Giuliano, 2009; Cojocaru, 2014), policy
preferences which also shape ones future opportunities.
   The goal of this paper is to provide empirical answers to both these questions by
taking advantage of the LiTS survey, which provides harmonized, comparable, and
nationally representative attitudinal data for 35 countries in the Europe and Central
Asia region. For the purpose of answering the above questions, the LiTS survey offers
a number of distinct advantages. First, it offers an unambiguous assessment of the
respondent’s own expectations of future mobility. Second, the LiTS questionnaire
makes it possible to construct an analytically appealing measure of inequality of
access to opportunities, based on expressed beliefs about the importance of personal
connections for getting access to key opportunities such as a good job or university
education; this measure of inequality of opportunity being in the spirit of the Second
Principle of Justice postulated by John Rawls. Third, in addition to beliefs about the
importance of connections, the survey also has responses on whether respondents have
access to personal connections that can facilitate access to opportunities. Finally, it
makes it possible to examine the link between inequality of access to opportunities
and expectations of future mobility based on comparable data from a large set of
countries; it also allows for comparisons between countries in Western and Eastern
Europe.
   By examining, empirically, the links between inequality of access to opportunity
and expectations of future mobility, the paper aims to contribute to the literature
that examines how expectations of future mobility are formed. While many factors
can be at play, as shown both in the theoretical and empirical studies reviewed in
Section 2, the focus of this paper is on the institutional dimensions of expectations /
aspirations, namely on the extent to which the existence of an uneven playing field
dampens such expectations, particularly for the disadvantaged groups. The subject
of inquiry is related to the studies that show that inequality of opportunity may elicit
behavioral responses such as resignation and reduced ambition, which can lead to




                                           3
inequality traps (Piketty 1995; World Bank 2005; Bourguignon et al. 2006).1
       The estimates presented in this paper appear to suggest that: (i) lack of connec-
tions is indeed associated with expectations of a lower position on the future social
ladder; and (ii) when informal connections are unavailable, it matters for your fu-
ture expectations whether you perceive connections to be vital or not. There is also
some evidence that in the European Union countries, where formal institutions are
stronger, individuals are less likely to resort to informal institutions such as personal
connections, even when these are available. Finally, there is also some evidence that
perceptions of unequal access to opportunities are linked with inter-generational mo-
bility, and with stronger redistributive preferences.
       The rest of the paper is structured as follows. Section 2 reviews the literature on
the determinants of future mobility expectations, and of experienced mobility. Section
3 provides a description of the key variables used in the paper as well as key descriptive
statistics. Section 4 outlines the empirical setup and the key hypotheses to be tested.
Key results are presented in section 5. Some alternative specifications are considered
in Section 6 as part of robustness analysis. Section 7 discusses some extensions of
the analysis, namely unequal access to opportunities in the intergenerational context
and with respect to individual preferences for redistribution. Section 8 provides some
concluding remarks.


2. Inequality of opportunity and mobility: Theory and evidence

       The American Dream holds that everyone in the United States can achieve suc-
cess and prosperity through hard work. The expectation that everyone can “make it”
with hard effort – an enduring national ethos – does not necessarily correspond with
observed reality – the degree of socio-economic mobility in the United States today
is relatively low, indeed lower than in some Nordic countries (OECD, 2010; Alesina,

   1
       This paper is also related, more generally, to studies that highlight the link between deprivation
and under-investment in human capital (Appadurai, 2004; Alsop et al. 2006; Hoff and Pandey,
2006).



                                                     4
Stancheva and Teso, 2016), and has been declining overtime (Chetty et al., 2016;
Davis and Mazumder, 2017). The fact that perceptions (can) diverge from reality is
important, as individuals will express support for particular policies based on their
perceived costs and benefits, which may differ from actual intent or outcomes. For
instance, Alesina, DiTella and MacCulloch (2004) find income inequality to be neg-
atively associated with life satisfaction in Europe but not in the United States, and
suggest that the difference is driven by perceptions of greater social mobility in the
United States. Alesina, Stancheva and Teso (2016) find respondents in the US to be
overoptimistic about mobility and Europeans to be over-pessimistic about mobility
vis-a-vis observed experience.
   Theoretical models have shown the possibility of the existence of multiple equilib-
ria, oftentimes referred to as European (low aspirations, effort /high redistribution)
and American (high aspirations, effort / low redistribution). For instance, in a model
of dynastic learning, Piketty (1996) shows that when experimentation to discover
true returns to effort is costly, individuals will learn from own past experience, such
that those who receive negative shocks can rationally get discouraged and supply less
effort, even when everyone starts off with the same initial beliefs and supplying the
same amount of effort. Perceptions of (un)fairness, once established, can be trans-
mitted across generations, and thus tend to persist overtime. Besley (2016) shows
that aspirational parents will choose to motivate their children to have aspirational
beliefs. Parents can also choose (rationally) to suppress “bad news” about low returns
to effort and pass on to children an optimistic worldview (Benabou and Tirole, 2006)
– a theoretical prediction that also has empirical backing from a recent study that
shows that in the US, right-wing respondents do not update their mobility beliefs
when presented with discouraging information about mobility (Alesina, Stancheva
and Teso, 2016). Alesina and Angeletos (2005) show that when income is a function
of talent, investment, effort and luck (noise), and when agents derive disutility from
unfair social outcomes and have a social demand for fairness, multiple stable equilib-
ria can arise. Thus, societies with a history of high distortions tend to have a higher
degree of unfairness in the income distribution, making aggressive redistribution de-


                                          5
sirable. This is because anticipation of high taxes induces agents to exert low effort;
as the result of this, the bulk of income heterogeneity in the distribution is due to
luck, which in turn makes it optimal ex post to redistribute.
   The 2006 World Development Report on Equity and Development provides a rich
account of how political, social, and economic inequalities combine to stifle social
mobility and create inequality traps (World Bank, 2005). Furthermore, empirical ev-
idence from around the world suggests that an important part of overall inequalities
in outcomes, commonly measures in the space of incomes or household expenditures,
is, in fact, due to inequality of opportunity, or inequality due to differences in cir-
cumstances for which an individual would not normally be held responsible, and
thus inequality that is objectionable on normative grounds (Bourguignon et al., 2003;
Roemer et al., 2003; Ooghe et al., 2007; Checchi and Peragine, 2010; Cogneau and ,
Mesple-Somps; Ferreira and Gignoux, 2008; Ferreira et al., 2008, 2010; Lefranc et al.,
2008, Lefranc et al., 2009).
   This paper aims to contribute to this literature, but its focus is somewhat different
– it examines the link between perceived inequality of opportunity and perceived fu-
ture mobility. I am not aware of other studies that examine directly the links between
subjective perceptions of inequality and subjective expectations of mobility. Clearly,
actual and perceived inequalities are correlated, although not perfectly. Figure 1 plots
perceived inequality of opportunity against available estimates of relative inequality
of opportunity from the Equalchances.org database. Likewise, actual and perceived
mobility are also correlated, even if imperfectly, as theoretical models have demon-
strated. This is also consistent with empirical evidence. Earlier studies have found
actual occupational mobility to be an important predictor of perceived occupational
mobility (Kelley and Kelley, 2009), and parental social class to be correlated with oc-
cupational aspirations of adolescents and with parental aspirations for their children
(Schoon and Parsons, 2002; Guyon an Huillery, 2016). Those who experienced mo-
bility personally tend to have more positive views about the chances of children born
in low income families to have high incomes when they grow up (Alesina, Stancheva
and Teso, 2016). Entrenched poverty has been shown to lead to depression (Case and


                                           6
Deaton, 2009), it can diminish goals and lead to hopelessness (Bryan, Chowdhury and
Mobarak, 2012; Hoff, 2012), and diminish one’s capacity to aspire (Appadurai, 2002).
Yet, as the discussion above illustrates, the distinction between perceived and actual
inequality (and mobility) is important because when the two diverge, individuals will
act on their perceptions when making their policy choices or other decisions.
   Why are diminished expectations of future mobility on account of inequality of
opportunity a concern? This is because diminished expectations can, in turn, lead to
decisions that can create vicious circles and inequality traps. For instance, mothers’
aspirations have been found to matter for children’s educational outcomes, especially
for children from poorer backgrounds (Serneels and Dercon, 2014). Poor Mexican
youths with higher future mobility expectations were more likely to stay in school
longer, exercise, use condoms during sex, and engage less in self-destructive behavior
such as consumption of alcohol, junk food, paying for sex, physical fighting, and
excessive TV (Weintraub et al., 2015). Social stigma, associated with immobility
at the bottom, greatly discourages school enrollment among low-caste children in
Pakistan, with low-caste girls, the most educationally disadvantaged group, being the
worst affected (Jacoby and Mansuri, 2015). In laboratory experiments with high and
low caste boys in India, providing cues to one’s place in the caste order was found
to influence the ability of low caste boys to learn and the willingness of high caste
boys to expend efforts (Hoff, Pandey 2014). Training aimed to improve self-image of
a socially-excluded group (sex workers in India) was found to improve health choices
and savings outcomes 15 months post-intervention (Ghosal et al., 2016). In other
words, actual mobility and perceived mobility are jointly determined; experienced
mobility affects one’s perceptions of mobility, while one’s perceptions of mobility
shape beliefs, policy preferences and behaviors (such as investments in human capital),
that can influence future mobility outcomes. The detrimental effects of inequality
of opportunity on development outcomes we value can be twofold – both direct,
by restricting individuals’ opportunity sets, and indirect, by affecting individuals’
expectations of (and aspirations for) the future, and the decisions / preferences that
rely on those expectations and aspirations.


                                          7
3. Data description

      The analysis in this paper relies on data from the Life in Transition Survey (LiTS),
administered by the World Bank and the European Bank for Reconstruction and
Development (EBRD). LiTS provides data from a unified survey for the entire set
                              2
of Transition Economies,          and five Western European countries (France, Germany,
Italy, Sweden, and the United Kingdom). For each of the countries, the LiTS survey
provides a nationally-representative sample of households; in each household the re-
sponses are based on a face-to-face interview with a randomly-selected member of the
household.3 Data from the second round of the survey, collected in 2010, are used in
this paper. A newer round of data was collected in 2016, but the questionnaire from
the third round omits one of the two key variables used in the analysis, namely the
question whether respondents have access to connections (see the empirical strategy
section below for details).
      The notion of expected socio-economic mobility is defined here based on the re-
spondents’ assessment of their position on the society’s 10-step welfare ladder today
and four years hence. These are derived from the respondent’s answers to the fol-
lowing questions: “Please imagine a ten-step ladder where on the bottom, the first
step, stand the poorest 10% people in our country, and on the highest step, the tenth,
stand the richest 10% of people in our country. On which step of the ten is your
household today? And where on the ladder do you believe your household will be
4 years from now?” The distribution of responses to the current and future welfare
ladder questions for the pooled sample is shown in Table 1. One can observe cluster-
ing of responses in the middle of the scale for both questions. About 60 percent of
respondents in the sample place themselves on the 4th, 5th, or 6th step of the welfare
ladder today, and more than 50 percent place themselves on one of these three steps
on the future welfare ladder. This higher density in the middle of the welfare ladder

  2
      No data are available for Turkmenistan. Mongolia and Turkey are excluded from the analysis
given the focus on Transition Economies.
   3
     The details of the sampling methodology can be found on the EBRD website at
http://www.ebrd.com/downloads/research/surveys/LiTS2eh.pdf


                                                8
is observed not only in the pooled sample, but also in the individual country samples.
       In order to construct a measure of inequality of opportunity, I rely on the respon-
dents’ assessments of the importance of “having connections” in order to progress in
a number of crucial dimensions of life, based on the following set of questions: “Some
people, because of their job, position in the community or contacts, are asked by
others to help influence decisions in their favor. In general, how important is it in
our country to have the support of such people to influence decisions in the following
situations?” The following domains of life are considered in the survey: (i) to get a
good job in the government sector; (ii) to get a good job in the private sector; (iii)
to get into university; (iv) to settle a dispute with a neighbor; and (v) to obtain
permits or official papers. The respondents could choose from the following options:
not important at all, somewhat important, moderately important, very important,
and essential. Only 3 percent of respondents in the pooled sample think that con-
nections are not important at all, such that there appears to be a universal belief
that connections are at least somewhat important to get ahead in various domains
of life. In the analysis that follows inequality of opportunity is defined as consistent
with the belief that connections in any of the above areas are either very important
or essential. This cutoff is arbitrary, but is consistent with the belief that fair access
to government positions, or education etc. is severely constrained.
       Inequality of opportunity as defined here is thus in the spirit of John Rawls. Recall
that the second part of the Second Principle of Justice proposed by Rawls (1971)
requires that offices and positions in society be open to all on a fair basis.4 This is
precisely what is queried by the above survey questions, since need for connections
to get jobs in various sectors, or to get necessary permits for business activity is in

   4
       The two principles of justice proposed by Rawls are as follows: First Principle - “each person is
to have an equal right to the most extensive total system of equal basic liberties compatible with a
similar system of liberty for all”; and Second Principle - “Social and economic inequalities are to be
arranged so that they are both: (a) to the greatest benefit of the least advantaged, consistent with
the just savings principle, and (b) attached to offices and positions open to all under conditions of
fair equality of opportunity.” (Rawls, 1971: p.302).



                                                    9
direct contradiction of the Second Principle as it denies equal access to all.
       The perceptions of inequality of opportunity are quite widespread in the region.
For instance, almost half of the adults in the region believe that it is very important
or essential to have connections to get a good government job, in Croatia and in
FYR Macedonia the share exceeds three quarters, and in Serbia it is greater than 80
percent. On the other hand, in the United Kingdom and in Sweden no more than
20 percent of adults share this view. In some of the transition countries the need for
connections to get a good public sector job is also perceived to be low, such as in
Estonia, Kyrgyzstan, Moldova, Tajikistan and Uzbekistan where less than one-third
of adults believe that connections are very important or essential for public sector
jobs. The need for connections is generally perceived to be lower in other domains of
life, although the share of adults who believe that connections are necessary in these
other areas remains non-trivial in most countries (Table 2).5
       The first part of Rawls’s Second Principle of Justice allows for inequalities to exist
to the extent that they are to the greatest benefit of the least advantaged. This is
not the case in practice. In the LiTS survey the respondents are further asked if they
knew of anyone (friends, relatives, classmates, local boss, etc.) who could influence
decisions with respect to getting a good government job, or getting into university
etc., should such influence be needed. Overall in the LiTS survey 32 percent of the
adult population reported that they do not know any such person, but this share is
generally higher for individuals who place themselves at the bottom of the welfare
ladder, or those who (or whose parents) had low levels of education. It is perhaps
not surprising that disadvantaged groups are least likely to thrive in the presence of
inequality of opportunity. These two characteristics – the importance of connections
to get ahead and lack of such connections – combine to create what Bourguignon et
al. (2006) call “inequality traps” or the persistence of relative positions (and implicitly

   5
       The last column in Table 2 is our measure of inequality of opportunity, which, for each individual
evaluates to 1 if connections in any of the five areas are very important or essential, and zero
otherwise.




                                                    10
of poverty and vulnerability) over time.
   In addition to the above variables, the LiTS survey also provides data on a num-
ber of beliefs, including beliefs about the importance of effort and luck for success,
preferences for the market economy and the respondent’s degree of risk aversion. The
summary statistics for the variables employed in the empirical analysis in section 4
are presented in Table 3.


4. Empirical strategy

   In order to investigate whether perceived inequality of opportunity dampens ex-
pectations of future mobility, the following relationship is estimated:



                    M obilityi = δ1 Ci + δ2 Ai + δ3 Ci Ai + Xi γ + εi ,             (1)

 where M obilityi is the expected future mobility, as represented by the difference

between the expected future position of the socio-economic ladder and the current
position of the same ladder, Ci is a dummy that equals 1 if connections are deemed
vital and zero otherwise, Ai is a dummy that equals 1 if connections are not available
and zero otherwise, Xi is a vector of control variables described in detail below, and
errors εi are allowed to be correlated within primary sampling units.
   Recall that the question this study proposed to examine was whether perceptions
of unequal access to opportunities dampen one’s expectations of future mobility. An
important caveat, and one that informs the empirical setup described here, is that
the LiTS data are cross-sectional, such as there are no readily-available sources of ex-
ogenous variation to identify a causal effect of (perceived) inequality of opportunity
on expected future mobility. In this sense, the results presented in Sections 5-7 of
this paper should be treated as correlational, rather than strictly causal. However,
there are several ways to address the omitted variable bias. First, note that it may
be problematic, in trying to examine the link between perceived inequality of oppor-
tunity and perceived future mobility, to compare mobility expectations of those who
perceive connections to be vital with those of the group who perceive connections

                                            11
not to be vital. This is because both the perceptions of inequality of opportunity and
expectations of future mobility may be correlated with some other difficult to measure
personal trait. For instance, general pessimism may affect both evaluations of future
mobility and of institutional fairness. For this reason, the analysis takes advantage of
the availability of responses on whether someone has connections or not, which allows
us to compare two groups of individuals, one with connections and other without, but
who provide similar answers to question on the necessity of connections. Similarly,
when looking at the importance of having connections, we can compare within the
group of those individuals who think that connections are needed. It is harder to
think of omitted variables that may affect comparisons between these groups. The
interaction of Ci and Ai creates four groups, the average predicted values for which
are as follows, denoting the constant term as δ0 :
           XXX
                 XXX
                        XXX      Availability
                              XXX                    Yes          No
            Connections             XXX
                                       XX
                                        X
            Vital                               δ0 + δ1    δ0 + δ1 + δ2 + δ3
            Not vital                                δ0         δ0 + δ2


   More formally, the following two hypotheses are examined:

   • Hypothesis 1: δ2 + δ3 = 0, i.e. when there is inequality in access to opportunities,
     having connections does not improve prospects of future upward mobility;

   • Hypothesis 2: δ1 + δ3 = 0, i.e. when connections are unavailable, inequality of
     opportunity is not associated with lower expectations of future mobility.

Furthermore, given the cross-sectional nature of the data, a number of important
confounding factors need to be accounted for in the model, in order to address en-
dogeneity concerns. Here the empirical strategy is to account explicitly in the Xi
vector for a number of factors expected to influence expectations of mobility, guided
by existing theoretical and empirical evidence. For this purpose, it is useful to have
in mind a heuristic model of expected mobility, which can be thought of as a function
of the following: (i) perceptions of inequality of opportunity (which is the interest

                                          12
here); (ii) relevant personal characteristics (e.g. age, education, employment); (iii)
current status on the socio-economic ladder; (iv) past mobility experience; (v) past
shocks; (vi) the degree of personal risk aversion; and (vii) luck. Below we motivate
the importance of accounting for these confounding factors.
   Certain personal characteristics, such as the person’s education and employment
status have been shown to have a strong effect on social mobility (Bozeat et al. 2010;
Narayan, Van der Weide et al., 2018). The respondent’s age needs to be included
in the model to account for the fact that there may be greater scope for younger
individuals to move up the ladder in the future, compared to those who are nearing
retirement. Similarly, the respondent’s sex and religious affiliation can be included
to account for possible differences in ambition between men and women, or across
religious denominations, which may lead to different aspirations for the future.
   It is the case the respondents who are currently at the top of the current welfare
ladder have less scope of moving up the ladder, and similarly those at the bottom are
less likely to move lower still in the near future. Moreover, the current position on
the welfare ladder can be correlated with the person’s assessment of the importance
of having connections to succeed in the labor market or in terms of education.
   In addition, the individual’s past mobility experience may influence future ex-
pectations. Here past mobility (upward, stable or downward) is derived from the
comparison of the current welfare ladder position with the past welfare ladder po-
sition. It is difficult to say a priori how past experience may translate into future
expectations. It may be, for instance, that past upward (downward) mobility may in-
dicate further upward (downward) mobility in the future. It is also possible, however,
that upward (downward) mobility in the past leaves less scope for further upward
(downward) mobility in the future. The direction of the effect is likely to depend
on other characteristics of the individual and is investigated empirically by including
dummies indicating either upward or downward past mobility (no past mobility being
the reference category).
   Given that the data were collected in 2010, expectations of future mobility may
be influenced by the recent financial crisis experience. Those who were affected by


                                          13
the crisis but believe its impact to be transitory may expect to move up the ladder in
the next four years as part of regaining the lost status due to the crisis. It is similarly
possible that those who were strongly affected by the crisis in a way that is not easy to
recover from over the short term may have modest expectations of upward mobility
in the future. To account for such confounding effects, the model controls for the
respondent’s assessment of the degree to which she has been affected by the financial
crisis.
    It is also important to account for the individual’s degree of risk aversion, since
those who are less risk averse may be more likely to engage in risky projects and expect
to move up the ladder based on their belief of their success. Risk averse individuals,
on the other hand, may be more likely to prefer stability, which in turn may lead
to expectations of a stable position on the society’s welfare ladder in the future. To
account for the individual’s degree of risk aversion, I include dummies based on a
hypothetical drought scenario. In the LiTS respondents are asked to respond to the
following hypothetical: “I will now ask you another hypothetical question. Imagine
that you are a farmer. If all goes well, you expect to sell your harvest for [insert
country specific amount] in a few more months. However, there is a risk: If there is
a drought the harvest will be lost – this has happened to your neighbors in half of
the recent years. You consider installing an irrigation system which would protect
your crop in case of a drought, but it costs [insert country specific amount] and you
would need to sell your car to buy it. Which of the following is more likely to be your
decision? (a) I would take the risk and hope there is no drought; (b) I would sell
my car and buy an irrigation system.” I distinguish in the empirical analysis between
these two groups, where group (a) captures those who are not averse to idiosyncratic
shocks, and group (b) captures those who are risk averse.
    The literature on inequality of opportunity generally distinguishes between in-
equality due to unequal opportunities, and inequality due to effort (see Ferreira et al.
2008, 2010 and references above). However, as noted by Lefranc et al. (2009), luck
is also an important factor, but generally gets bundled together with effort. In the
LiTS survey it is possible to account for the influence of luck by conditioning on the


                                            14
individual’s beliefs with regard to the reasons why there are people in need in society,
whether it be luck, laziness, an inevitable part of modern life, or injustice in society.
   Finally, the Xi vector also includes country dummies, such that estimates rely on
within-country variation. The full set of controls is listed in Table 3.


5. Results

   Before proceeding with the discussion of the results related to the hypotheses
outlined in section 4, I return to the fact that the estimates are based on the second
wave of the LiTS survey from 2010, and a newer (2016) wave of the survey was
published recently. As noted above, the analysis relies on the 2010 round of the
survey because the key variable in the analytical set-up, namely a question whether
someone has access to connections, was not repeated in the 2016 survey questionnaire
and is only available for the 2010 data. Nevertheless, it is worth commenting on
the persistence over time of beliefs regarding inequality of access to opportunities, or
beliefs about future mobility to see whether the beliefs expressed in 2010, and hence
some of the conclusions that could be drawn from the empirical analysis in this paper,
are still relevant six years hence.
   Figure 1 presents the distribution of responses to the need for connections ques-
tions, separately for each domain, for the 2010 and 2016 survey rounds. In the overall
sample, the distribution of beliefs with respect to the need for connections remains
largely unchanged. If anything, the views are more pessimistic still in 2016, as mea-
sured by the share of adults who think that connections are either very important or
essential across various domains of opportunity. Across countries, the average share
of adults who believe access to opportunities to be unequal in the sense of the defini-
tion in this paper, the views are quite similar in countries in which the incidence of
inequality of access to opportunities was already relatively high in 2010; for many of
the countries in the lower end of the 2010 distribution one can see significant shifts
toward more pessimistic views between 2010 and 2016. Finally, the countries that
had relatively pessimistic expectations of future mobility in 2010 are still largely at
the bottom of the distribution of mobility expectations in 2016, with some notable ex-

                                           15
ceptions such as Ukraine and Russian Federation (and to a smaller degree Armenia),
where the adverse economic conditions in recent years, and military conflict in the
case of Ukraine, are reflected in the sharply lower expectations with respect to future
socio-economic mobility. In other words, there is a considerable degree of stability in
the region with respect to the beliefs about equality of opportunity; similarly, even
though data from the 2010 round of the survey were collected in the aftermath of
the financial crisis, which may have altered individuals beliefs about mobility (in the
empirical analysis I will account for this explicitly), these beliefs also appear to be
reasonably stable rather than transitory.
   Having these inter-temporal patterns in mind, the estimates from the empirical
specification in (1) are presented in Table 4. The results are presented for the pooled
sample of countries, and also, separately, for the European Union member states
and Non-EU countries. To some degree this distinction between EU and non-EU
countries is arbitrary. The results are reported for these country groupings for the
following reasons: (i) because this is a standard division of countries in publications
based on LiTS survey data, inclusively in the publications by EBRD that rely on
LiTS data; (ii) given the focus on institutional aspects, the distinction is meaningful
analytically in the sense that in EU countries formal institutions may be stronger, and
similarly in non-EU countries reliance on informal institutions (such as connections,
for instance) may be more prevalent. I will return to this below when I discuss the
use of connections.
   Column (1) of table 4 presents the estimates of regressions for the pooled LiTS
sample. Both hypotheses appear to be rejected by the data. First, when there is
inequality of access to opportunities, connections matter (δ2 + δ3 < 0), meaning that
expectations of future mobility are lower in the group that views connections to be
vital but does not have any connections, in comparison with the group that similarly
views connections to be vital to get ahead, and does indeed possess such connections.
Second, when connections are unavailable, it matters whether the playing field is level
(δ1 + δ3 < 0), in other words, expectations of future mobility are lower in the group
that views connections as vital to get ahead and does not have them, as compared to


                                            16
another group, also without connections, but which does not view such connections
as helping to secure important opportunities in life.
   Both hypotheses are similarly rejected in the estimates for the group of non-EU
countries in column (3), whereas inside the EU (column 2), it appears that when
access to opportunities is perceived to be unequal, expectations of future mobility
appear to be similar among those with connections and those without. I return to
this below.
   What do the magnitudes of the estimated coefficients imply? When there is in-
equality in access to opportunities, lack of connections is associated with a 0.11 points
reduction in expected future mobility. This should be viewed against the fact that
the overall level of expected mobility, as measured by the difference in the future and
current ladders, is quite small – in the pooled sample the mean difference between
the future and the current ladders is 0.27, such that the reduction in expected future
mobility is notable. In the non-EU countries, average expected mobility is higher,
0.69, such that the higher estimated coefficient in absolute terms is actually smaller
in relative terms, but still not trivial, at more than 25 percent.
   Returning to the estimates in Table 4, several other factors appear to be salient
for expectations of future mobility, as suggested by the heuristic model of mobility
described above. Upward mobility in the past is associated with expectations of
further upward mobility in the future. The same is true of past downward mobility
in non-EU countries, but not in the EU countries, where the estimated coefficient on
the downward past mobility is negative. One interpretation that is consistent with
this difference is that perceptions of downward mobility in the EU are perceived to be
of a less transitory nature. It could be that a more stable economic environment in
the EU may leave less scope for those who perceive to have moved downward in the
past to expect a reversal of their fortunes in the immediate future. It is not possible,
however, to confirm this with the LiTS data. Willingness to take risks is also positively
associated with future mobility expectations outside of the EU, whereas this is not
the case in EU countries. On the other hand, the belief that need is the product of
laziness is positively associated with future mobility expectations only in the EU.


                                           17
   Some other factors have similar effects in both country groupings. A stronger effect
of the recent financial crisis is associated with lower future mobility expectations. The
belief that need in society is the product of injustice (the reference category being
“inevitable part of modern life”) also is associated with lower expectations vis-a-vis
future upward mobility.
   The estimates on other variables (not reported to conserve space) suggest that in
both groups of countries expectations of future upward mobility diminish with age,
are higher in urban areas and for those who are not married. In the EU they are also
higher at higher levels of education, whereas outside the EU they are higher for those
currently employed (whereas there are no differences across education levels). Men
and women have similar aspirations of upward mobility once other characteristics and
beliefs are held constant.
   The fact that connections do not help when they are both deemed to be important
and available in the EU is an interesting finding that deserves further investigation.
One possible reason for this could be due to the fact that it may be less common -
and possibly less socially acceptable - to rely on informal connections in the Euro-
pean Union. One would certainly expect reliance on informal institutions to be more
prevalent when formal institutions are weaker. It is possible to test this conjecture
with LiTS data. The respondents who claimed to have connections were asked how
likely they would be to rely on these connections. In the EU sample 18 percent of
respondents reported that it was “not at all likely” that they would resort to personal
connections if they had them (29 percent in Western European countries), whereas
in the non-EU Transition Economies only 10 percent of respondents reported that
they would not resort to connections if they had them (8 percent in CIS countries).
The distribution of responses for each country is provided in Figure 4. To investigate
this further, I split the group who think that connections are vital and report having
them) into two categories – those who say that they will very likely or definitely use
their connections, and the rest, whose appeal to connections, even if available, is less
certain. Otherwise, the model is the same as in table 4. More formally:



                                          18
 M obilityi = δ1 Ci + δ2 Ai + δ3 Ci Ai + δ4 U sei + δ5 U sei Ci + δ6 Ai U sei + δ7 Ci Ai U sei + Xi γ + εi (2)


    In other words, the relationship in (2) is the same as in (1) except that it now has
a triple interaction between perceptions of inequality Ci , availability of connections Ai
and the use of connections U sei , where U sei is a dummy variable that equals 1 when
the respondent would use connections very likely or definitely, and zero otherwise.
Note that in practice terms Ai U sei and Ci Ai U sei in (2) above (coefficients δ6 and
δ7 ) are not estimated because these are empty sets – the use variable is only defined
for the group of respondents who report having connections. Table 5 reports two key
hypothesis tests: (i) δ2 + δ3 = 0 and (ii) (δ2 + δ3 ) − (δ4 + δ5 ) = 0. The first one
looks at the difference between the group that views the connections to be vital and
does not have such connections, and the group with similar beliefs about inequality
of access to opportunities, but with connections, although they are not likely to use
these connections despite having them. The second test replaces the latter group
with the group who has connections and is indeed likely to resort to them. The
results are consistent with the above conjecture – in the EU countries, there is no
statistically significant difference between future mobility prospects between those
without connections and those with connections, but only when these connections are
not resorted to; not having connections when the playing field is not level is indeed
associated with lower mobility expectations relative to the group with connections
who do intend to use them.


6. Robustness analysis

    The measure of inequality of access to opportunities defined in this paper and
used in the empirical analysis is all-encompassing by construction, as a union of all 5
domains (of opportunities) that are available in the data. This is even though one may
argue that not all five domains may be of equal importance, and therefore it is not
clear why they should be treated equally in the construction of a measure of overall
inequality of access to opportunity. Indeed, if we look at the incidence of unequal


                                                     19
access across the five domains in Table 2, it is clear that inequalities in the areas of
obtaining a good government job, or a good private sector job, are considerably more
prevalent than perceived inequalities related to obtaining permits or settling disputes.
   I have chosen a union measure in part to avoid situations in which the overall
binary measure of inequality of opportunity is evaluated to zero, even though in one
of the domains, permits for instance, the respondent views connections to be of utmost
importance. One may still argue that given the low incidence of perceived inequalities
in the areas of getting permits, or settling disputes, and given their less obvious
connections to prospects of future mobility for an average person, and also their
theoretical connection to the Rawlsian formulation, namely “offices and positions”
open to all, it may be more precise, and closer to the spirit of the concept of inequality
of access to opportunities if it were defined over the space of the main opportunities
only – getting a job (either government or private) and getting university education.
   As part of the robustness analysis, I define an alternative measure of inequality of
access to opportunities defined over the three main areas of opportunities, as described
above. The two measures are plotted against one another in Figure 4 and can be seen
to be strongly correlated, with the IO measure constrained to 3 domains mainly
shifting the overall level of perceived inequality of opportunity somewhat downward,
but preserving, for the most part, the ranking of countries in the sample by the
overall level of inequality of opportunity. Table 6 reports the model estimates from
the baseline empirical specification reported in Table 4, with the only difference being
that the measure of inequality of access to opportunities here is the more restricted
measure. The results are qualitatively the same as those reported in Table 4 with
respect to the main hypotheses that are being tested. Moreover, the magnitudes of
the estimated differences between various groups, captured by δ2 + δ3 and by δ1 + δ3
are larger, which would be consistent with the argument that the more restricted
measure of inequality of access to opportunities is less noisy in a relevant sense.
   As a further robustness test, it is also possible to relax some of the other assump-
tions in the empirical analysis. For instance, in the regressions discussed until now,
the coefficients on the other variables included in the X vector were constrained to be


                                           20
constant across the four population groups defined by the variables reflecting respon-
dent beliefs about access to opportunities and availability of connections. This can
be relaxed by estimating the model of mobility separately for each of the four popu-
lation groups, and then computing predicted mobility values for the whole sample for
each of the estimated coefficient vectors – this is a potential outcome means setup.
Then differences in the means can be used as an estimate of what in the treatment
literature is defined as the “average treatment effect”, although we do not adopt the
formal causal treatment framework here.
   These estimates are given, separately for the main definition of inequality in access
to opportunities (Table 7) and the alternative definition described above, that relies
only on the main three areas of opportunities (Table 8). In both tables, the population
group without connections and who believe connections to be vital is taken as the
baseline group, and the predicted expected mobility is reported for this baseline,
while for the other three groups the tables report the predicted increment in expected
mobility relative to baseline, including the empirical counterparts to Hypothesis 1
and Hypothesis 2 (but now with minus signs because a different group forms the
baseline), as well as the difference between the baseline group and the group with
connections and who do not think these connections to be vital. The estimates still
reject hypothesis 1 – when connections are vital to get ahead, having connections,
relative to not having connections, is associated with higher expectations of future
socio-economic mobility, in the overall sample and in the non-EU group of countries.
We fail to reject either hypothesis in the EU group of countries; as was noted earlier,
this is related to the propensity of actually relying on connections, when these are
available. The data similarly reject hypothesis 2 – when connections are not available,
expected mobility is lower if connections are perceived to be vital to get ahead. It can
also be seen from the estimates that expected mobility is highest for the group that
does not believe connections to be vital, but has those connections anyway – in the
overall sample the expected future mobility in this group is almost 50 percent higher
than in the baseline population.



                                          21
7. Extensions

   So far, the analysis has focused on the relationship between inequality in access to
opportunities and intra-generational mobility, based on one’s assessment of expected
socio-economic mobility in the near future. An interesting question to ask is how this
relationship may apply, or not, to the inter-generational mobility context. Another
angle that can be explored, in addition to the link between perceived IO and mobility
expectations, is whether IO is also linked with current preferences for redistribution.
For instance, individuals may support more redistribution today if they feel that they
may not be able to move up the socio-economic ladder as much because of unequal
access to opportunities, as they may be more amenable to the government’s efforts
to aid those at the bottom. The inter-generational context is explored in section 7.1,
whereas preferences to redistribution are discussed in Section 7.2.

7.1. Unequal access to opportunities and inter-generational mobility

   Inequality of opportunity is particularly pernicious to the extent to which it gen-
erates immobility (or persistence) not only within a single generation, but across
generations, such that children born to disadvantaged parents at the bottom of the
income distribution are stuck at the bottom of the income distribution in their gener-
ation through no fault of their own, but on account of circumstances that they have
no control over.
   To investigate the inter-generational mobility context with the LiTS data I rely on
responses to the question “To what extent do you agree with the following statement:
children who are born now will have a better life than my generation” with responses
ranging from “strongly disagree” to “strongly agree” on a five-step Likert scale. About
one third of adults in the LiTS sample either agree or strongly agree with the asser-
tion that children will have a better life than the current generation. Interestingly,
perceptions of intra-generational mobility and inter-generational mobility are strongly
related in the data (Figure 5). Those who expect themselves to be upwardly mobile
in the near future are also more likely to be more positive with respect to the mobility
prospects of children, with a correlation coefficient of 0.78.

                                          22
       Perceived inter-generational mobility is also correlated with estimates of actual
inter-generational mobility from the World Bank’s Global Database of Intergenera-
tional Mobility (GDIM) for the countries in the LiTS sample (Figure 6). Countries in
which the share of adults who think that children will do better than the current gen-
eration is lower tend also to have higher estimates of inter-generational persistence,
indicating lower inter-generational mobility.6
       The link between inequality of access to opportunities and inter-generational mo-
bility is estimated based on the same model as before, where the dependent variable is
instead a binary (above neutral) measure of inter-generational mobility that evaluates
to 1 if the respondent agrees or strongly agrees that children will have a better life
than the current generation, and zero otherwise. The estimates are reported in Table
9. The estimates reveal that when connections are unavailable, perceived unequal ac-
cess to opportunities is associated with lower inter-generational mobility (Hypothesis
2, or δ1 + δ3 = 0 is rejected by the data). Similarly, in the overall sample, when access
to opportunities is not equal, lack of connections is associated with lower perceived
inter-generational mobility (δ2 + δ3 = 0 is rejected).
       It should be noted that the results are a bit noisier than in the case of intra-
generational mobility. This is not entirely surprising since intra-generational mobility
expectations are more immediate and for these, current assessments of inequality of
opportunity may be more pertinent. Moreover, while intra-generational expectations
are personal, in the sense that they are based on one’s own mobility expectations
for the future, the assessment of inter-generational mobility is general – it refers to
comparisons of children in general with the current generation (again, in general),
rather than prompting respondents to report mobility expectations for their own
children in particular. Given the reasonably strong relationship between assessments
of intra- and inter-generational mobility in the data, it is quite possible that one’s

   6
       The measure of intergenerational persistence is based on the coefficient from the regression of
children’s years of education on the education of their parents, using ten-year age cohorts. The
estimates in Figure 5 are for the most recent, 1980s birth cohort. For more details, see Narayan,
Van der Weide et al. (2018).


                                                  23
own children or children from one’s reference group whose conditions may be similar,
probably receive greater weights in one’s evaluation of children’s future chances in
general, how exactly respondents frame their answers to this survey question is not
clear. Still, the results can be cautiously viewed as reinforcing the main results of the
analysis, as well as the predictions of theoretical models discussed in section 2, that
link inequality in access to key opportunities in life to lower expectations of future
mobility; moreover, these lower expectations may be relevant not only in the context
of the immediate future, but rather may persist over time, and across generations,
thus perpetuating existing inequality traps.

7.2. Inequality in access to opportunities and redistributive preferences

   If access to key opportunities in life is perceived to be unfair, on account to whom
you know, then resulting inequalities in society are likely to be similarly perceived to
be unfair. This is especially likely to be the case for those who do not have connec-
tions that may facilitate access to opportunities such as jobs or university education.
When inequalities are perceived to be unfair, individuals may be more likely to desire
a greater amount of redistribution in society to compensate for such unfair distribu-
tion of rewards (see Cojocaru, 2014 for empirical evidence of the link between fairness
and inequality aversion based on LiTS data). It is possible to explore with LiTS data
whether the “Rawlsian” inequality of opportunity examined in this analysis is asso-
ciated with stronger redistributive preferences. The latter are elicited in the survey
questionnaire by way of the following statement “The gap between the rich and the
poor in our country should be reduced”, with which the respondents can either agree
or disagree on a 5-step Likert scale that ranges from “strongly disagree” to “strongly
agree”. Using responses to this question I construct a binary variable that evaluates
to 1 for above neutral responses (either agree or strongly agree) and zero otherwise.
The model is re-estimated with the preference for reducing the gap between the rich
and the poor as the dependent variable, and the δ vector corresponds, as before, to
the intersection of beliefs about the importance of connections and whether one has
such connections, as in the baseline model reported in table 4. The results, reported


                                           24
in Table 10, suggest that both inside and outside the EU the perceived existence of
inequality of opportunity is associated with stronger redistributive preferences when
connections are not available (δ2 + δ3 = 0 is rejected) and also that when connections
are unavailable, inequality of opportunity is associated with stronger preferences for
redistribution, asδ1 + δ3 = 0 is similarly rejected both in the overall sample and in
the regional country sub-samples.


8. Concluding remarks

   Given the importance of future mobility aspirations for current redistributive pref-
erences, and also for important current decisions such as those related to investments
in human capital, which then influence future mobility prospects, this paper looked
at the link between inequality of access to opportunities, defined as the perceived
need of connections to get ahead, and expectations of future socio-economic mobility.
Inequality of opportunity is perceived to be widespread in transition economies, and
especially outside of the European Union. I find that lack of connections is associated
with expectations of a lower position on the future social ladder when connections
are perceived to be vital. Similarly, when informal connections are unavailable, it
matters for your future mobility expectations whether you perceive connections to be
vital or not. These results appear to be robust to meaningful changes in the definition
of inequality of access to opportunities, as well as differences in model specification.
Notably, in the EU sub-sample, availability of connections does not necessarily offset
the negative association of inequality of opportunity and future mobility expecta-
tions. It appears that this is due to the fact that not everyone who has connections
intends to use them, and there is greater reluctance to use connections in the EU,
consistent with there being stronger formal institutions in place, which would make
reliance on informal institutions less desirable and/or socially acceptable. The link
between inequality of opportunity and future mobility also carries over from the intra-
generational setting to the inter-generational mobility setting, as lack of connections,
when the playing field is not level, is associated with more pessimistic views about
the success of children born today vis-a-vis the current generation. Finally, inequality

                                          25
of opportunity is also found to be associated with stronger redistributive preferences
both in EU member states and in the non-EU group of countries.


9. Acknowledgments

   The author is grateful to Andrew Clark, Ambar Narayan, Branko Milanovic, Carol
Graham, Christoph Lakner, Daniel Gerszon Mahler, Ivan Torre, Madiha Afzal, Mau-
rizio Bussolo, Peter Murrell, Rakesh Gupta N. Ramasubbaiah, Roy Van der Weide,
Silvia Redaelli, Stefan Thewissen, and to the participants of the 2018 International
Development Ethics Association (IDEA) conference, the Equal Chances: Equality
of Opportunity and Social Mobility Around the World conference, and the IBS and
World Bank conference on Globalization, Work, and Distributional Tensions in Eu-
rope and Central Asia for helpful comments and suggestions, and to the European
Bank for Reconstruction and Development (EBRD) for access to the data. All re-
maining errors are mine alone. The views expressed in this paper are those of the
author and should not be attributed to The World Bank Group or any affiliated
organization.




                                         26
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                      Table 1: Current and future welfare ladder placement
                                                   Future ladder
Current ladder       1        2      3       4       5       6     7       8     9    10    Total
1                  795     160      96      32      43      19     8       9     1     8    1,171
2                  441     946     348     162     117      46    25      16     8     4    2,113
3                  307     711 1,767       912     595     243   118      51    24    18    4,746
4                   91     326     775   2,053   1,426     785   358     163    33    32    6,042
5                   67     159     440     947   3,380 1,693 1,098       502   109    84    8,479
6                    7      14      65     198     519 1,546     985     547   145    71    4,097
7                    2        4     19      42     107     262 1,022     562   211    72    2,303
8                    2        1      6      13      26      42   100     373   172   101      836
9                    1        0      0       1       3       2    10      21    78    41      157
10                   2        0      0       0       2       2     2       3     8    79       98
Total           1,715 2,321 3,516        4,360   6,218 4,640 3,726     2,247   789   510   30,042
Notes: Eestimates for the full sample.




                                                 32
                         Table 2: Importance of having connections
                                 Gov    Private    Univ    Permits   Disputes   IO
     Albania                     0.47   0.28       0.25    0.30      0.19       0.70
     Armenia                     0.68   0.52       0.46    0.38      0.21       0.76
     Azerbaijan                  0.56   0.39       0.22    0.15      0.11       0.69
     Belarus                     0.41   0.37       0.21    0.11      0.07       0.51
     Bosnia and Herzegovina      0.62   0.51       0.52    0.34      0.35       0.73
     Bulgaria                    0.78   0.70       0.39    0.58      0.40       0.83
     Croatia                     0.79   0.55       0.37    0.25      0.37       0.83
     Czech Reoublic              0.37   0.34       0.18    0.22      0.25       0.61
     Estonia                     0.31   0.35       0.06    0.06      0.08       0.45
     FYROM                       0.77   0.46       0.45    0.51      0.36       0.88
     France                      0.40   0.48       0.16    0.25      0.28       0.69
     Georgia                     0.42   0.37       0.13    0.10      0.09       0.51
     Germany                     0.46   0.41       0.13    0.09      0.14       0.58
     Hungary                     0.70   0.67       0.25    0.23      0.23       0.79
     Italy                       0.50   0.38       0.16    0.16      0.13       0.61
     Kazakhstan                  0.55   0.45       0.28    0.25      0.17       0.63
     Kosovo                      0.36   0.25       0.29    0.24      0.20       0.54
     Kyrgyzstan                  0.25   0.17       0.32    0.27      0.05       0.50
     Latvia                      0.71   0.69       0.04    0.07      0.06       0.76
     Lithuania                   0.49   0.41       0.12    0.11      0.10       0.58
     Moldova                     0.27   0.22       0.22    0.15      0.11       0.39
     Montenegro                  0.53   0.39       0.27    0.21      0.18       0.60
     Poland                      0.34   0.27       0.18    0.15      0.14       0.48
     Romania                     0.51   0.40       0.16    0.20      0.19       0.58
     Russian Federation          0.55   0.48       0.30    0.22      0.13       0.68
     Serbia                      0.82   0.65       0.36    0.37      0.35       0.86
     Slovak Republic             0.50   0.41       0.29    0.23      0.26       0.73
     Slovenia                    0.63   0.46       0.15    0.17      0.23       0.75
     Sweden                      0.15   0.29       0.04    0.06      0.13       0.40
     Tajikistan                  0.32   0.30       0.41    0.35      0.30       0.69
     United Kingdom              0.19   0.19       0.10    0.16      0.19       0.41
     Ukraine                     0.49   0.44       0.35    0.24      0.13       0.64
     Uzbekistan                  0.29   0.25       0.40    0.28      0.21       0.52
     Total                       0.45   0.40       0.21    0.19      0.17       0.60

Notes: Share of adults reporting that connections are very important or essential in each
of the five opportunity domains. The IO column reports a union measure based on
whether connections in any one domain are deemed to be very important or essential.




                                            33
                       Table 3: Summary statistics by region

                                 EU              Non-EU               Total
The gap between rich and poor should be reduced
   Strongly disagree           0.0252 (0.157)     0.0348    (0.183)   0.0301   (0.171)
   Disagree                    0.0581 (0.234)     0.0716    (0.258)   0.0651   (0.247)
   Neither agree nor disagree 0.130 (0.336)        0.138    (0.345)    0.134   (0.341)
   Agree                       0.416 (0.493)       0.445    (0.497)    0.431   (0.495)
   Strongly agree               0.371 (0.483)      0.310    (0.463)    0.340   (0.474)
Inequality preference (1-10)   6.563 (2.680)       6.353    (3.078)    6.454   (2.895)
Welfare ladder (current)        4.654 (1.669)      4.420    (1.619)    4.533   (1.647)
Welfare ladder (future)         4.759 (1.968)      5.181    (2.170)    4.977   (2.086)
Ln(HH expenditures)             5.633 (1.264)      4.603    (1.148)    5.100   (1.310)
Main determinant of need in society today
   Unlucky                      0.104 (0.305)     0.0915    (0.288)   0.0975   (0.297)
   Laziness                     0.224 (0.417)      0.207    (0.405)   0.215    (0.411)
   Injustice                    0.406 (0.491)      0.487    (0.500)   0.448    (0.497)
   Inevitable part of life      0.197 (0.398)      0.141    (0.348)   0.168    (0.374)
   Other                       0.0680 (0.252)     0.0729    (0.260)   0.0706   (0.256)
Mobility over the past 4 years
   Downward past mobility       0.389 (0.487)      0.313    (0.464)   0.349    (0.477)
   No past mobility             0.418 (0.493)      0.422    (0.494)   0.420    (0.494)
   Upward past mobility         0.193 (0.395)      0.265    (0.442)   0.231    (0.421)
How much were you impacted by the financial crisis?
   A great deal                 0.139 (0.346)      0.197    (0.398)   0.169    (0.375)
   A fair amount               0.267 (0.443)       0.269    (0.443)    0.268   (0.443)
   Just a little                0.308 (0.462)      0.174    (0.379)    0.239   (0.426)
   Not at all                   0.261 (0.439)      0.291    (0.454)    0.276   (0.447)
   Don’t know                  0.0248 (0.156)     0.0694    (0.254)   0.0479   (0.214)
Risk aversion hypothetical
   Would take the risk         0.339 (0.473)       0.354    (0.478)   0.347    (0.476)
   Would not take the risk      0.569 (0.495)      0.473    (0.499)   0.519    (0.500)
   Don’t know                  0.0916 (0.288)      0.173    (0.378)   0.134    (0.341)
Age                             49.03 (17.14)      43.18    (16.72)   46.00    (17.18)
Female                          0.586 (0.493)      0.605    (0.489)   0.596    (0.491)
University education            0.216 (0.411)      0.198    (0.398)   0.206    (0.405)
Employed                       0.557 (0.497)       0.477    (0.499)   0.515    (0.500)
Ln(HH size)                     0.752 (0.536)      1.107    (0.574)   0.936    (0.584)
Household composition
   Children’s share in HH       0.115 (0.197)      0.165    (0.212)   0.141    (0.207)
   Female share in HH           0.537 (0.296)      0.530    (0.242)   0.534    (0.269)
   Elderly share in HH          0.144 (0.314)     0.0736    (0.231)   0.108    (0.277)
Market is preferred             0.343 (0.475)      0.380    (0.485)   0.362    (0.481)
Non-Orthodox                    0.856 (0.351)      0.516    (0.500)   0.680    (0.466)
Not married                     0.465 (0.499)      0.363    (0.481)   0.413    (0.492)
Rural                          0.343 (0.475)       0.447    (0.497)   0.397    (0.489)
Observations                   14154              15888               30042
Note: Mean of each variable with standard deviation in parentheses.




                                         34
                      Table 4: Inequality of opportunity and mobility expectations

                                                         Overall         EU       Non-EU
          δ1                                            -0.058**     -0.083**       -0.055
                                                         (0.028)      (0.033)      (0.042)
          δ2                                           -0.107***    -0.115***     -0.106**
                                                         (0.031)      (0.035)      (0.052)
          δ3                                              -0.009       0.064        -0.074
                                                         (0.037)      (0.043)      (0.061)
          Present welfare ladder                       -0.159***    -0.165***    -0.154***
                                                         (0.008)      (0.010)      (0.013)
          Need due to: inevitable part of life              ref.         ref.         ref.
          Unlucky                                          0.028      0.069*        -0.005
                                                         (0.038)      (0.041)      (0.065)
          Laziness                                       0.071**     0.074**        0.064
                                                         (0.032)      (0.034)      (0.056)
          Injustice                                    -0.130***    -0.140***     -0.115**
                                                         (0.029)      (0.029)      (0.052)
          Other                                           -0.051       -0.058       -0.043
                                                         (0.045)      (0.058)      (0.068)
          I would sell my car and buy irrigation            ref.         ref.         ref.
          I would take the risk                           0.038*       -0.031     0.104***
                                                         (0.022)      (0.026)      (0.035)
          Don’t know                                      -0.063     -0.134**       -0.003
                                                         (0.039)      (0.059)      (0.050)
          Crisis had no impact                              ref.         ref.         ref.
          A great deal                                 -0.329***    -0.301***    -0.343***
                                                         (0.038)      (0.051)      (0.052)
          A fair amount                                -0.154***    -0.181***    -0.124***
                                                         (0.028)      (0.032)      (0.042)
          Just a little                                   -0.028      -0.050*       -0.000
                                                         (0.024)      (0.027)      (0.040)
          Don’t know                                   -0.173***      -0.105*    -0.190***
                                                         (0.043)      (0.062)      (0.054)
          No past mobility                                  ref.         ref.         ref.
          Downward past mobility                        0.193***       -0.012     0.387***
                                                         (0.027)      (0.030)      (0.044)
          Upward past mobility                          0.227***    0.161***     0.283***
                                                         (0.027)      (0.033)      (0.039)
          R-squared                                       0.193        0.142        0.165
          Obs                                             30188        14230        15958
          δ2 + δ3                                         -0.116       -0.050       -0.180
          Prob>|t|                                         0.000        0.106        0.000
          δ1 + δ3                                         -0.067       -0.018       -0.129
          Prob>|t|                                         0.026        0.585        0.016

Notes: Robust standard errors, clustered at primary sampling unit level in parentheses.
Regressions also include the following set of controls: Ln(HH expenditures), crisis impact,
age and age squared, sex, education, Ln(HH size), household composition, religion, marital
status, area of residence and country dummies. Significance: * p<0.1, ** p<0.05, ***
p<0.01.



                                                  35
                  Table 5: Differentiating by likelihood of using connections

                                             Overall       EU       Non-EU
                 δ1                         -0.071**   -0.102***     -0.064
                                             (0.030)    (0.036)     (0.044)
                 δ2                        -0.101***   -0.119***    -0.095*
                                             (0.032)    (0.036)     (0.054)
                 δ3                           0.004      0.084*      -0.066
                                             (0.039)    (0.046)     (0.063)
                 δ4                           0.074      -0.044       0.115
                                             (0.065)    (0.095)     (0.088)
                 δ5                           0.031       0.121      0.001
                                             (0.072)    (0.109)     (0.097)
                 R-squared                    0.193      0.140       0.166
                 Obs                          30042      14154       15888
                 δ2 + δ3                      -0.097     -0.034      -0.161
                 Prob>|t|                     0.001       0.299      0.001
                 (δ2 + δ3 ) - (δ4 + δ5 )      -0.201     -0.111      -0.277
                 Prob>|t|                     0.000       0.038      0.000

Notes: Robust standard errors, clustered at primary sampling unit level in parentheses.
Regressions include the same full set of controls like the baseline model. Significance: *
p<0.1, ** p<0.05, *** p<0.01.




                                              36
                       Table 6: Using a more restrictive measure of IO

                                      Overall          EU     Non-EU
                      δ1             -0.064**      -0.073**    -0.071*
                                      (0.028)       (0.032)    (0.042)
                      δ2            -0.107***     -0.103***   -0.111**
                                      (0.030)       (0.033)    (0.052)
                      δ3               -0.011        0.053      -0.075
                                      (0.037)       (0.043)    (0.062)
                      R-squared        0.193         0.140       0.165
                      Obs              30042         14154      15888
                      δ2 + δ3          -0.117        -0.050     -0.186
                      Prob>|t|         0.000          0.123     0.000
                      δ1 + δ3          -0.075        -0.020     -0.146
                      Prob>|t|         0.015          0.560     0.007

Notes: Robust standard errors, clustered at primary sampling unit level in parentheses.
Regressions include the same full set of controls like the baseline model. Significance: *
p<0.1, ** p<0.05, *** p<0.01.




                                             37
                    Table 7: Regression adjustment, main definition of IO

                                          Overall       EU       Non-EU
                  -(δ1 + δ2 + δ3 )       0.175***    0.159***    0.197***
                                          (0.028)     (0.034)     (0.042)
                  -(δ2 + δ3 )            0.088***      0.040     0.125***
                                          (0.023)     (0.028)     (0.036)
                  -(δ1 + δ3 )             0.054*       0.020      0.096*
                                          (0.032)     (0.034)     (0.052)
                  IO, no connections     0.378***    0.056***    0.666***
                                          (0.020)     (0.021)     (0.032)
                  Obs                      30187       14229       15958

Notes: Robust standard errors in parentheses. Outcome model include the same full set of
controls like the baseline model. Significance: * p<0.1, ** p<0.05, *** p<0.01.




                 Table 8: Regression adjustment, alternative definition of IO

                                          Overall       EU       Non-EU
                  -(δ1 + δ2 + δ3 )       0.181***    0.141***    0.224***
                                          (0.027)     (0.034)     (0.042)
                  -(δ2 + δ3 )            0.092***      0.044     0.129***
                                          (0.024)     (0.030)     (0.037)
                  -(δ1 + δ3 )             0.070**      0.023      0.125**
                                          (0.031)     (0.034)     (0.052)
                  IO, no connections     0.371***    0.054**     0.654***
                                          (0.020)     (0.023)     (0.033)
                  Obs                      30187       14229       15958

Notes: Robust standard errors in parentheses. Outcome model include the same full set of
controls like the baseline model. Significance: * p<0.1, ** p<0.05, *** p<0.01.




                                             38
                         Table 9: IO and intergenerational mobility

                                     Overall        EU     Non-EU
                        δ1            -0.009      -0.004    -0.016
                                     (0.010)     (0.012)   (0.014)
                        δ2            0.009        0.016     0.000
                                     (0.012)     (0.015)   (0.018)
                        δ3           -0.027*     -0.034*    -0.018
                                     (0.014)     (0.018)   (0.021)
                        R-squared     0.145       0.110      0.134
                        Obs           30114       14176     15938
                        δ2 + δ3       -0.018      -0.018    -0.018
                        Prob>|t|      0.063        0.184     0.199
                        δ1 + δ3       -0.037      -0.037    -0.034
                        Prob>|t|      0.002        0.019     0.060

Notes: Robust standard errors, clustered at primary sampling unit level in parentheses.
Regressions include the same full set of controls like the baseline model. Significance: *
p<0.1, ** p<0.05, *** p<0.01.




                                            39
              Table 10: Inequality of opportunity and redistributive preferences

                                     Overall          EU     Non-EU
                       δ1           0.059***      0.069***   0.052***
                                     (0.010)       (0.012)    (0.015)
                       δ2           0.038***      0.054***     0.020
                                     (0.012)       (0.014)    (0.019)
                       δ3             -0.009        -0.026     0.012
                                     (0.013)       (0.016)    (0.021)
                       R-squared      0.064          0.074     0.064
                       Obs            29242         13952      15290
                       δ2 + δ3        0.029          0.028     0.032
                       Prob>|t|       0.001          0.022     0.012
                       δ1 + δ3        0.050          0.042     0.063
                       Prob>|t|       0.000          0.002     0.000

Notes: Robust standard errors, clustered at primary sampling unit level in parentheses.
Regressions include the same full set of controls like the baseline model. Significance: *
p<0.1, ** p<0.05, *** p<0.01.




                                             40
                                                                                                                                                        0
                                                                                                                                                       35
                                                                                                                                                       45




                                                                                                                                                        5
                                                                                                                                                       10
                                                                                                                                                       15
                                                                                                                                                       20
                                                                                                                                                       25
                                                                                                                                                       30
                                                                                                                                                       40
                                                                                                                                Not important at all
                                                                                                                               Somewhat important
                                                                                                                               Moderately important
                                                                                                                                    Very important
                                                                                                                                           Essential




     opportunity domains.
                                                                                                                                Not important at all
                                                                                                                               Somewhat important
                                                                                                                               Moderately important
                                                                                                                                    Very important
                                                                                                                                           Essential




                                                                                           Government job Private sector job
                                                                                                                                Not important at all
                                                                                                                               Somewhat important
                                                                                                                               Moderately important
                                                                                                                                    Very important
                                                                                           University




41
                                                                                                                                           Essential
                                                                                                                                Not important at all
                                                                                                                               Somewhat important
                                                                                                                               Moderately important
                                                                                                                                                                      Figure 1: Perceived need for connections across domains




                                                                                           Dispute




                                                                                                                                    Very important
                                                                                                                                           Essential
                                                                                                                                Not important at all
                                                                                                                               Somewhat important
                                                                                                                               Moderately important
                                                                                           Permit




                                                                                                                                    Very important
                                                                                                                                           Essential
                                                                                                                                                        2016
                                                                                                                                                               2010




     Notes: Distribution of responses in the pooled sample for each of the survey rounds
     (2010 and 2016) regarding the importance of connections for each of the
                        Figure 2: Perceived IO and actual IO are not one and the same

                                                              IT
         .45




                                                                                                 BG
         .4




                                                     RO
            .35
   IO, relative




                                                                                           HU

                                       EE

                                          PL
  .3




                                                                                                 HR
                                                                   FR                 LV
                        SE
                   GB                              CZ
                                                        LT                       SI
         .25




                                                                         SK

                                                             DE
         .2




                  .3           .4              .5             .6            .7              .8
                                    IO in access to good jobs and education


Notes: The graph plots, for each country in the sample, the share of adults who
perceive connections to be either very important or essential in any of the five domains
of opportunities, including government jobs, private sector jobs, university education,
resolving a dispute or getting a permit, against available estimates of inequality of
opportunity from the Equalchances.org database. See also the EBRD Transition
Report 2016-2017 for more details on the latter.




                                                        42
                 Figure 3: Overall inequality in access to opportunities across countries

    Moldova
     Estonia
 Kyrgyzstan
      Poland
     Belarus
    Georgia
 Uzbekistan
     Kosovo
   Lithuania
   Romania
   Germany
         Italy
 Montenegro
      Czech
     Ukraine
 Kazakhstan
  Azerbaijan
      Russia
   Tajikistan
     Albania
    Slovakia
          BiH
    Slovenia
       Latvia
    Armenia
    Hungary
     Croatia
    Bulgaria
      Serbia
    FYROM

                 0              .2              .4              .6               .8

                                           IO 2010        IO 2016
                                           EO 2010        EO 2016



Notes: The graph plots, for each country in the sample and for each of the survey
rounds (2010 and 2016), the share of adults who perceive connections to be either
very important or essential in any of the five domains of opportunities, including
government jobs, private sector jobs, university education, resolving a dispute or
getting a permit.




                                                     43
                       Figure 4: Expected future mobility across countries


   Romania
         Italy
    Slovenia
    Hungary
      Czech
     Croatia
   Germany
   Lithuania
      Serbia
  Azerbaijan
      Poland
       Latvia
     Estonia
    Slovakia
          BiH
    Bulgaria
    Armenia
     Ukraine
      Russia
    FYROM
     Belarus
    Moldova
     Kosovo
 Montenegro
     Albania
 Kazakhstan
    Georgia
 Kyrgyzstan
 Uzbekistan
   Tajikistan

                 −.5        0           .5           1           1.5         2

                                             2010     2016



Notes: The graph plots, for each country in the sample and for each of the survey
rounds (2010 and 2016), the mean of the raw difference between the expected future
societal ladder position and the current position on the same ladder. The difference
equals to zero if the future ladder and the current ladder are unchanged, and can
range from -9 to +9.




                                               44
                       Figure 5: Use of connections, when available

    Azerbaijan
   Uzbekistan
   Kyrgyzstan
       Belarus
     Lithuania
      Moldova
       Ukraine
   Kazakhstan
        Russia
     Tajikistan
      Bulgaria
      FYROM
        Serbia
       Estonia
   Montenegro
        France
      Slovakia
        Poland
        Czech
         Latvia
            BiH
     Romania
      Georgia
      Hungary
       Croatia
      Armenia
       Albania
      Slovenia
       Kosovo
             UK
     Germany
           Italy
      Sweden

                   0   20             40                 60          80      100
                                               Percent

                                  Not at all likely           A bit likely
                                  Likely                      Very likely
                                  Definite / certain




Notes: The graph plots, for each country, the distribution of responses to the ques-
tion “And how likely is that you would actually ask for such help?”, defined over
respondents who report having connections.




                                               45
                          Figure 6: IO measures over 5 and 3 domains

         .9
                                                                                            MKD
                                                                                            SRB
                                                                                         HRV
                                                                                         BGR
         .8



                                                                                   HUN
                                                                               ARM
                                                                                 LVA
                                                                              SVN
                                                                      SVK
                                                                        BIH
              .7
  IO, 5 domains




                                                        TJK   FRA
                                                               ALB    AZE
                                                                     RUS

                                                             UKR
                                                              KAZ
                                                CZE       ITA
     .6




                                                           MNE
                                                       ROU
                                                       DEU
                                                      LTU

                                              KSV
                                             UZB
                                               GEO
                                              BLR
         .5




                                            KGZ
                                         POL
                                        EST

                        GBR
         .4




                              SWE MDA



                   .2             .4                     .6                        .8
                                         IO, 3 domains


Notes: The graph plots the country mean IO measure based on all 5 domains available
in the survey questionnaire against an IO measure based on three main domains
(government job, private sector job and university education). Each dot represents
the country average of an indicator variable that evaluates to 1 if either the 5-domain
IO variable or the 3-domain IO variable evaluates to 1, and zero otherwise.




                                               46
                                                           Figure 7: Intra- and inter-generational mobility

                                                                                                                           TJK
                                                                                                                          UZB
                      1.5
                                                                                  KGZ
                                                                                               GEO
  Perceived intra−generational mobility




                                                                                                           KAZ

                                                                                         MNE                            ALB
                              1




                                                                                                                  KSV
                                                             MDA
                                                                                         BLR
                                                                                        MKD
                                                                               RUS
                  .5




                                                                               UKR
                                                            ARM
                                                                                        BGR
                                                                     BIH SVK
                                                                             LVA AZE      EST    POL
                                                             SRB
                                                                                                     LTU
                                                     DEU    HRV
      0




                                                                   CZE
                                                     HUN
                                           SVN ITA
                                          ROM
                      −.5




                                          .2                .3              .4            .5                 .6           .7
                                                                 Perceived inter−generational mobility


Notes: Intra-generational mobility is based on the difference between the future and
current societal ladders. The inter-generational mobility measure is an indicator vari-
able that evaluates to 1 if the respondent answers agree or strongly agree to the
statement “Children who are born now will have a better life than my generation”
and zero otherwise.




                                                                                   47
                                     Figure 8: Actual and perceived intergenerational mobility in transition economies

                   .7           .6          ROM
   Inter−generational persistence




                                                    HUN
                                                                     BGR
                                                                       MNE
                                                                      MKD
                      .5




                                                       ARM
                                                       MDA
                                                       SRB BIH
                                                       HRV               GEO

                                                                   AZE
                                                                  RUS
            .4




                                                                                           ALB
                                                                LVA
                                                              SVK UKR                    KSV
                                                           CZE
                                                                   KGZ
                                                                             POL
                                             SVNITA                                KAZ
                                                                       EST
                                                                       BLR
  .3




                                                                             LTU
                                                    DEU


                                                                                             TJK
                                                                                            UZB
                   .2




                                            .2                .4                  .6               .8             1
                                                 Perceived mobility of children vis−a−vis current generation


Notes: Perceived intergenerational mobility based on the LiTS question whether
children who are born now will have a better life than my generation. See also
figure 5 for details.                                      Actual inter-generational mobility is based on data from
equalchances.org databased and is an inter-generational education elasticity measure.
See equalchanges.org for details.




                                                                               48