rafmacalaba/datause-encoder-data huggingface dataset:
# **TABLE A10: European Bank for Reconstruction and Development (EBR)**

## **A10: European Bank for Reconstruction and Development (EBR)**

http://www.ebrd.org The EBRD is an international organization which supports the transition towards open market-oriented economies and promotes private and entrepreneurial initiative in the countries of Central and Eastern Europe and the Commonwealth of Independent States (CIS). The EBRD is based in London.

The EBRD publishes an annual Transition Report, which includes a number of governance variables in its Transition Indicators and Survey of Legal Reforms. The Transition Report presents eight “Transition Indicators” representing "cumulative progress in the movement from a centrally planned economy to a market economy” for 26 transition economies. The subjective indicators are based on a checklist of various objective measures and reflect the views of EBRD staff.

Beginning in 1996, the EBRD has conducted in 26 countries a survey of local public officials, private firms, academics, lawyers, and other experts, in order to assess the progress made in financial legal reform in transition economies. The survey considered two areas of financial legal reform: banking and securities activities. For each area, two indices describing the extensiveness and effectiveness of the financial legal framework were developed, for a total of four ratings. The “extensiveness” ratings measure how closely legal rules affecting investment follow international standards. “Effectiveness” reflects how clear, accessible and adequatelysupported the legal rules are. Both are intended to provide a measure of how conducive the laws of these countries are to fostering investment. Both indices however were discontinued in 2003.

In this paper we use data from the 1996, 1998, 2000, and 2002-2005 Transition Reports. In the table below we list the variables included in each of the governance indicators.

|**Table A10: European Bank for Reconstructi**|2005<br>**on and Development(27**|2004<br>**trans**|2003<br>**ition**|2002<br>**econo**|2000<br>**mies**|1998<br> **)**|1996|
|---|---|---|---|---|---|---|---|
|**Voice and Accountability**||||||||
|NA|..|..|..|..|..|..|..|
|**Political Stability**||||||||
|NA|..|..|..|..|..|..|..|
|**Government Effectiveness**||||||||
|NA|..|..|..|..|..|..|..|
|**Regulatory Quality**||||||||
|Price liberalisation|X|X|X|X|X|X|X|
|Trade & foreign exchange system|X|X|X|X|X|X|X|
|Competition policy|X|X|X|X|X|X|X|
|Commercial Law Extensiveness|..|..|..|X|X|X|..|
|Commercial Law Effectiveness|..|..|..|X|X|X|..|
|Financial Regulations: extensiveness|..|..|..|X|X|X|..|
|Financial regulations: effectiveness|..|..|..|X|X|X|..|
|**Rule of Law**||||||||
|NA|..|..|..|..|..|..|..|
|**Control of Corruption**||||||||
|NA|..|..|..|..|..|..|..|

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that of control group in round June 1999 and November 1999 (while for round November 1998 we find third-order stochastic dominance; see also figure 3 where we report the estimated CDF’s and poverty deficit curves<sup>18</sup> ). An implication of these results is that in June and November 1999 P(0) (and so P(1) and P(2)) will be always smaller in treatment than in control group regardless of the poverty line chosen.

In conclusion, since we find the strongest evidence of poverty reduction when we analyze poverty gap and severity of the poverty index (poverty gap squared), which put greater weight on the poorest of the poor, both the simulation and the actual ex-post results suggest that the largest reductions in poverty of PROGRESA are being achieved in the poorest of the poor population.

# **6.  Conclusions**

Conditional cash transfer (CCT) programs aim to alleviate current poverty through monetary and in-kind benefits, as well as reduce future levels of poverty by encouraging investments in education, health and nutrition. The success of CCT programs at reducing current poverty depends on whether, and the extent to which, cash transfers affect adult work incentives.

Based on the experimental design of PROGRESA’s evaluation sample, our findings yield a very consistent answer. PROGRESA does not have any significant effect on adult labor supply choices. In particular, the results show that there has been no particular reduction in labor market participation rates, as may have been predicted by some economic models of behavior. There is some evidence that individuals, at least right after they started to receive the transfers,

> 18 The estimated CDF gives the P(0) for any level of income. Poverty deficit curve is defined as the area under the CDF up to some poverty line. If the poverty deficit curve of one distribution lies above the poverty deficit curve of another, the first distribution will always have more poverty according to the poverty-gap measure, P(1).

23
laboratory treatments and real-world bonus programs. Researchers generally confer low external validity to laboratory experiments and caution against the isolated interpretation of results derived from a single experiment.

The most recent attempts at addressing the issue of proper causal inference on performance pay and increasing the representativeness of results are RCTs. In an RCT researchers are able to randomize key features of an actual policy program that services the actual population of interest. The advantage of such a field experiment is the similarity of the target population, the structure of the incentive program, paired with the randomization of treatment. Although field RCT are time and resource intensive studies, several teams of researchers have implemented similar studies in different contexts around the world, considerably adding to the empirical understanding of performance pay.

# **4. The empirical literature reviewed**

Given that the literature has analyzed incentive pay for a broad set of jobs and utilizing an array of methodological approaches, the following presentation of the empirical literature in this paper is sorted by (a) the nature of the job, using Wilson‘s typology and (b) the methodological approach. In total 153 empirical studies of PRP (see the Appendix for the full list) were considered in this review, of which 110 are for craft and coping jobs (Table 2). The research to date on the subject has largely focused on advanced countries — in the review 127 studies are in OECD contexts, and only 26 are in developing country settings. The literature has also focused largely on craft jobs and production jobs, with no experimental studies to date on coping jobs.

**Table 2: Studies by country environment, methodology, and job type**

|**Country and methodology**|||**Types**|**of Jobs**|||
|---|---|---|---|---|---|---|
||**_Productionjobs_**|**_Proceduraljobs_**|**_Coping jobs_**|**_Craft jobs_**|**_Unclassified_**|**_Total_**|
|**_OECD study_**|**27**|**0**|**15**|**72**|**13**|**127**|
|Observational|14|0|15|59|13|101|
|Field RCT|7|0|0|13|0|20|
|Lab. experiment|6|0|0|0|0|6|
|**_Developing country study_**|**1**|**0**|**1**|**22**|**2**|**26**|
|Observational|0|0|1|15|2|18|
|Field RCT|0|0|0|6|0|6|
|Lab. experiment|1|0|0|1|0|2|
|**Total**|**28**|**0**|**16**|**94**|**15**|**153**|

## **Observational studies**

## **_Public sector coping jobs_**

Observational studies about performance-related pay for public sector coping jobs suggest somewhat limited effectiveness of this component of pay flexibility for these activities — they also focus overwhelmingly on OECD settings.

A series of OECD reports and associated discussion papers chronicle the type and extent of pay related civil service reforms in advanced industrialized countries (OECD 1993, 1996, 1997b; Kim 2002; Burgess and Ratto 2003; OECD 2004a, 2005a, b; Perry, Mesch, et al. 2006; Ketelaar, Manning, et al. 2007; Rexed, Moll, et al. 2007; OECD 2008, 2009; Perry, Engbers, et al. 2009). Generally, these refer to coping jobs in that they refer to, or imply that they are referring to, managers with complex tasks.

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# Table 7

# Decomposition of Change over Tine in Women's Fraction of the Labor **_Force,_** Within anG Between Sectors, by Region

|Sectors and<br>Region of<br>Countries|Women as<br>Average<br>a Fraction of Rate of Change<br>Labor Force<br>in Fraction(%)|Percent o<br>Intrasector<br>Change|f Chanae due<br>Intersector<br>Change|to:'<br>Residual<br>Interaction|
|---|---|---|---|---|
|Agricultural/Nonagri|clultural<br>Sectorsa||||
|World Sample|.31<br>-.31|102|4|-6|
|High Income|.36<br>.22|95|-7|12|
|Latin America|.24<br>.30|34|51|14|
|Africa|.14<br>-.13|147|7|-54|
|East Asia|.37<br>.29|97|5|-2|
|South & West Asia|.25<br>-1.21|96|5|-1|
|Agriculture and Sev|en Other SectorSb||||
|World Sample|.31<br>-.31|115|-12|-5|
|High Income|.36<br>.22|46|47|7|
|<br>Latin America|.24<br>.30|8|87|5|
|Africa|.14<br>-.13|123|29|-52|
|East Asia|.37<br>.29|96|2|2|
|South & West Asia|.25<br>-1.21|95|6|-2|

'Agriculture includes forestry and fishing.

bNonagriculture divided into the following ISIC categories: Mining; manufacturing; electricity, gas, and utilities; construction; wholesale and retail trade; transportation; business and personal services.

cPercent of changes due to the three components may not precisely sum to one because of rounding. The change in workers in wage employments is summed across countries before total changes in the share of wage earners are calculated and decomposed for the sample and for the regional aggregations of countries.

See Appendix Table A-1 for composition of sample.
# Table 18: Tests on pre-trends

||||||Non|-food|
|---|---|---|---|---|---|---|
||Total Con|sumption|Food Co|nsumption|Consu|mption|
||Waves||Waves||Waves||
||<br>2 & 3|Pre-Trend|<br>2 & 3|Pre-Trend|<br>2 & 3|Pre-Trend|
|_Access to_:|||||||
|Medium or strong 3G/4G|-0.054|0.028|-0.075*|0.043|-0.013|0.023|
||(0.036)|(0.038)|(0.043)|(0.044)|(0.034)|(0.039)|
|Medium or strong 3G/4G|0.048|0.027|0.046|0.043|0.044|0.036|
|for one year|(0.033)|(0.029)|(0.038)|(0.034)|(0.031)|(0.031)|
|<br>Medium or strong 3G/4G|<br>0.099***|<br>0.008|<br>0.120***|<br>0.011|<br>0.039|<br>0.032|
|<br>for two years or more|(0.033)|(0.030)|(0.038)|(0.036)|(0.032)|(0.032)|
|Medium or strong 3G/4G|0.152***|-0.023|0.169***|-0.015|0.104***|-0.012|
|for three years or more|(0.032)|(0.030)|(0.037)|(0.035)|(0.031)|(0.030)|
|# of observations|9,022|8,580|9,022|8,580|9,022|8,580|
||||||Labo|r force|
||Povert|y $1.90|Povert|y $3.20|partic|ipation|
||Waves||Waves||Waves||
||2 & 3|Pre-Trend|2 & 3|Pre-Trend|2 & 3|Pre-Trend|
|_Access to_:|||||||
|Medium or strong 3G/4G|0.004|0.010|0.015|-0.017|-0.021|-0.015|
||(0.027)|(0.029)|(0.022)|(0.024)|(0.019)|(0.017)|
|Medium or strong 3G/4G|-0.037|-0.031|-0.007|-0.017|-0.001|-0.004|
|for one year|(0.023)|(0.022)|(0.020)|(0.020)|(0.016)|(0.015)|
|<br>Medium or strong 3G/4G|<br>-0.072***|<br>-0.013|<br>-0.042**|<br>-0.010|<br>0.016|<br>-0.003|
|<br>for two years or more|(0.023)|(0.023)|(0.021)|(0.020)|(0.016)|(0.015)|
|<br>Medium or strong 3G/4G|<br>-0.091***|<br>0.001|<br>-0.076***|<br>0.016|<br>0.021|<br>0.005|
|for three years or more|(0.022)|(0.022)|(0.021)|(0.021)|(0.015)|(0.014)|
|# of observations|9,022|8,580|9,022|8,580|27,349|25,445|
||Farm|self-|Wage/|salaried|Non-f|arm self-|
||emplo|yment|emplo|yment|empl|oyment|
||Waves||Waves||Waves||
||<br>2 & 3|Pre-Trend|<br>2 & 3|Pre-Trend|<br>2 & 3|Pre-Trend|
|_Access to_:|||||||
|Medium or strong 3G/4G|-0.011|0.004|-0.006|-0.010|0.008|-0.018|
||(0.023)|(0.020)|(0.006)|(0.009)|(0.014)|(0.014)|
|Medium or strong 3G/4G|<br>0.010|<br>-0.004|<br>-0.007|<br>0.005|<br>-0.005|<br>0.014|
|for one year|(0.019)|(0.016)|(0.006)|(0.008)|(0.010)|(0.012)|
|<br>Medium or strong 3G/4G|<br>0.020|<br>-0.008|<br>-0.009|<br>0.012|<br>-0.003|<br>0.012|
|<br>for two years or more|(0.018)|(0.016)|(0.007)|(0.008)|(0.011)|(0.013)|
|<br>Medium or strong 3G/4G|<br>0.013|<br>-0.011|<br>0.003|<br>0.006|<br>0.003|<br>0.012|
|<br>for three years or more|(0.018)|(0.015)|(0.007)|(0.008)|(0.010)|(0.012)|
|# of observations|27,348|25,431|27,348|25,439|27,347|25,433|

_Notes_ : Standard errors reported in parentheses are clustered by LGAs. *** p<0.01, ** p<0.05, * p<0.1.

27
to the w _ork & study_ Index. In other words, transitions are more common between _work only_ and _Nini,_ than between _work only_ or _Nini_ and _study only_ .

All in all, the history of past decisions regarding time use influences decisions regarding time use in the future, but as students leave school it is harder for them to go back, particularly if they have experienced Nininess.

# _(ii) Quintiles of household income per capita to proxy for youth income,_ ��

As Figure 7 shows, the relationship between quintiles of household income per capita and the probability of being _Nini_ is non-linear for men and inexistent for women aged 15 to 18 years old. Male youths from better-off households (those in the fifth quintile of the distribution of household income per capita) have a 8.1 p.p. lower probability of being _Nini_ compared to those in poor households (those in the first quintile, the comparison group). Quintiles 3 and 4 exhibit lower and similar (according to the confidence intervals) probabilities of being _Nini_ , while the probability for youth in quintile 2 is not statistically different from that of those in quintile 1, creating a non-linearity in the response. For women, although the same pattern is present (see Figure 7), there is not enough statistical confidence to distinguish these patterns from each other or from the first quintile.

Figure 7. Proportional Change in the Probability of Being Nini to HH Income Quintile changes, Base Group is Quintile 1, Youth Aged 15-18 y.o., by Gender (a) Male (b) Female <!-- Start of picture text --> 0.04 0.04<br>0.02 0.02<br>0.00 0.00<br>-0.02 -0.02<br>-0.04 -0.04<br>-0.06 -0.06<br>-0.08 -0.08<br>-0.10 -0.10<br>-0.12 -0.12<br>Q2 Q3 Q4 Q5 Q2 Q3 Q4 Q5<br><!-- End of picture text --> _Notes_ : The value of the bars represent the marginal effects on the probability of being Nini for the corresponding variables from the underlying estimation of multinomial logit models (one for each gender). The dependent variable in the multinomial models takes three states (Nini, Work Only, and Study Only). Only marginal effect for the outcome of Nini is presented in this graph. The models include controls for history of past decision indices, youth’s own education level, parental education level, household income quintiles, a set of demographic variables, and state economic condition variables. Complete results are presented in Appendix Table A1. _Source_ : Authors’ calculations based on model estimation using data from the _Encuesta Nacional de Ocupación y Empleo_ (ENOE), 2005:Q1 - 2013:Q4.

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relative prices, demographic factors and tastes. Differences in relative prices and (possibly) tastes between urban and rural areas could well be the most important factor mitigating the welfare interpretation of interhousehold differences in food shares in Indonesia. For this reason it is probably better to consider urban and rural areas separately.

Figure 4 gives the cumulative frequency distributions of the share of non-food goods in total consumption for each of urban and rural areas for each date. First-order dominance still holds up to high non-food shares, so a wide range of poverty lines and measures will continue to indicate a decrease in poverty in both sectors over this period. The proportion of the rural population with a food share in excess of 75 percent (a commonly used poverty line) fell from 39.2 percent in 1984 to 35.8 percent in 1987, while for the urban sector it fell from 10.5 to 8.5 percent. The decline is not as dramatic as that suggested by the CPI adjusted consumptio. and income data, but it is still evident in the distribution of food shares.

Did undernutrition also diminish? Figure 5 gives the distributions of calorie intake per person for the two dates. The 1987 distribution lies below that for 1984 up to a high intake level (the ranking only reverses for the upper nine percent of persons). First-order dominance thus holds up to high caloric norms. The "second-order dominance condition" discussed in Section 2 holds over the entire distribution, so that it can be concluded that a broad class of undernutrition measures show an improvement whatever the underlying distribution of requirements. These results were also found to hold in both urban and rural areas. The quantitative shift in the caloric intake distribution is quite substantial at the lower end; for example, the estimated proportion of the population consuming less than 1500 calories per day decreased from 37 percent in 1984 to 27 percent in 1987.
for transport costs (Fujita, 1989).<sup>9</sup> In our setting, introducing tenure insecurity, makes bid-rents flatter compared to the standard monocentric model without tenure insecurity,<sup>10</sup> which will have a dampening effect on equilibrium land prices.

As a result of Proposition 2, the bid rent Ψ _e_ can be defined piecewise over at most three zones in the city:

- In the central zone defined by _x ≤_ _<u>x</u>_ <u>(</u> _e_ ), the type- _e_ household chooses _π_<sup>_∗_</sup> ( _x, e_ ) = _πmax_ , the slope of the bid rent is _−πmaxt_ and the bid rent is a linear function of _x_ .

- In the peripheral zone defined by _<u>x</u>_ <u>(</u> _e_ ) _≤ x_ , the household chooses _π_<sup>_∗_</sup> = _πmin_ , the slope of the bid rent is _−πmint_ and the bid rent is a linear function of _x_ .

- For _<u>x</u>_ <u>(</u> _e_ ) _< x <_ _<u>x</u>_ <u>(</u> _e_ ), the bid rent is strictly convex.<sup>11</sup>

Over the portion of the city where the household would choose intermediate levels of tenure security, the convexity of the bid-rent function reflects the willingness to pay a higher land price for a plot marginally closer to the CBD, with the increment compensating for the marginal increase in tenure security in addition to the marginal saving in transport costs. This is represented on Figure 3 below. To continue our demonstration, we now establish the following Lemma by differentiating Equation (8) with respect to _e_ , and using the fact that _π_<sup>_∗_</sup> is a non-increasing function of _e_ (see Proposition 1). The intuition is that lower-type households demand higher levels of tenure security due to their advantage in terms of land administration fees. They thus have an incentive to bid more for a location marginally closer to the CBD.

> 9In the standard urban economics model, the Alonso-Muth-Mills condition strictly speaking actually equates the marginal transport cost increment with the marginal saving in land consumption. Our result in Equation (8) follows from the assumption that land consumption is constant and normalized to unity and accounts for the likelihood of keeping the plot (and having to commute to the city center). The standard urban economics model can thus be viewed as a specific case of our broader model under which tenure security is certain.

> 10Constraining _π⋆_ ( _x, e_ ) to be equal to 1 would lead the standard condition that _<u>∂∂x</u>_ <u>Ψ</u> _<u>e</u>_<sup>=</sup><sup>_−t_</sup> 11 _<u>∂</u>_<sup>2</sup> <u>Ψ</u> _<u>e</u>_ Since _∂x_<sup>2(</sup><sup>_x, ν_(</sup><sup>_e_)) =</sup><sup>_−t_</sup><sup>_<u>∂π</u>_</sup> _∂x_<sup>_∗>_0with</sup><sup>_<u>∂π</u>_</sup> _∂x_<sup>_∗<_0followingProposition1.</sup>

14
attendance rate of at least 80 percent in the preceding academic quarter.<sup>8</sup> At the time of program introduction, the value of the per-girl benefit was 14 percent of average monthly household consumption spending per adult equivalent in Punjab (or 15 percent of the corresponding average in rural Punjab).<sup>9</sup> Program benefits were transferred to households on a quarterly basis, with benefits for a given quarter delivered in the following quarter. The maximum individual transfer per quarter was PRs 600 (= PRs 200 × 3 months), offered for four quarters in a year.

Key steps in program administration began at the government school, where the head teacher was responsible for recording female students’ attendance for the quarter in a standard register as well as for determining their eligibility and the amount of their benefit. The teacher also filled in a money order form for each female student beneficiary. The school sent a copy of the completed register and the individual money order forms to the district education department, which transmitted the money orders to the government post service. The post service then delivered cash to beneficiary girls and households, typically at either the girls’ school or their home. In addition, district education departments would transmit data and documentation on beneficiary girls and cash delivery to the provincial education department.

A sample-based process evaluation conducted during the first year of the program by a government-contracted consulting firm finds that, while program implementation suffered from delays and was burdensome for different parties (including beneficiaries), all sample teachers and virtually all sample students and parents were aware of the attendance condition

> 8 Currency conversion is at the average exchange rate of PRs 58 per U.S. dollar in 2004. The benefit amount was estimated to cover safe travel to a government school with secondary grades, which in rural areas was typically located some distance from the girl’s village. While the program benefit is small in absolute terms compared with those in samples of CCT programs in developing countries that have been evaluated (Garcia and Saavedra 2017), the level of the benefit as a percentage of household consumption spending is within the range of benefit sizes in these samples (Baird et al. 2014; Benhassine et al. 2015).

> 9 Based on statistics from the 2004/05 Pakistan Household Income and Expenditure Survey. We are unable to estimate the program benefit level as a percentage of average household consumption spending per adult equivalent in program districts because available household sample surveys that gather data on income and consumption spending are not representative at the district level.

11