rafmacalaba/data-use-mentions-extended huggingface dataset:
In addition to the unconditional mean values illustrated above in this section, another simple way to compare homeowner self-assessments with the market rents paid by tenants is to estimate an ordinary least squares regression that provides the average size of the inaccuracy, conditional on a set of covariates. The analysis estimates this regression separately for each year and in Metropolitan Lima and in rural areas using the same set of covariates used in the matching exercise without the imposition of the overlap and common support conditions (Annex A, Table A.1). In Metropolitan Lima, a statistically significant difference is found between homeowner self-assessed values and the market rents paid by tenants in 6 of 15 years, and these years do not overlap with the survey years in which a statistically significant inaccuracy was detected through matching. Similarly, in the case of rural areas, ordinary least squares estimates find a statically significant difference between what estimated by homeowners and what tenants pay in 7 out of 15 years and only in 2012 and 2017 both ordinary least squares and matching estimators identified a statistically significant difference.

# **7. Conclusions**

This paper proposes the use of matching estimators to test the accuracy of the value reports of homeowners by making use of information from a typical household budget survey. The lack of supplemental sources, such as administrative data from national cadastres, is a common issue faced by researchers and practitioners working in developing countries.

The findings indicate that, in 2003–17, homeowners in Metropolitan Lima, on average, provided, with the exception of the two most recent years, accurate estimates of the housing services values of the dwellings they were living in, compared with tenants living in dwellings with observably similar characteristics. In rural areas, two matching algorithms, namely, kernel and nearest neighbor, do not achieve a good balance of the matched sample in the majority of the years considered. Homeowners did not provide accurate market rental values of their dwellings between 2014 and 2017 and underestimated the rental value on average by about −24 percent, a magnitude
Although education was, in principle, supposed to be devolved to local councils in 2005, the actual devolution of this sectoral function has been delayed due to significant resistance from the Ministry of Education. The first direct transfers to local council accounts for education were not released until 2007 (Casey, 2009). Given this delay, we expect the association between the quality of education and local councillors’ trustworthiness to be weaker than correlation between the quality of health care and councillors’ trustworthiness. We also expect the effect of education on councillors’ trustworthiness to be stronger in 2008 than in 2007. The community survey asked respondents whether there was a primary school in their community. If there was a primary school, respondents were asked who runs the school: the government; an NGO or mission; the community; or a private group. They were then asked a series of questions about the quality of the school’s infrastructure including the type of roof over the school and whether there is a latrine at the school. Respondents were also asked several questions about access to education and perceptions of its quality. If respondents have a child that goes to primary school, they were asked whether the school provides textbooks for free. The survey probed respondents about their level of satisfaction with the school: In general, are you satisfied with 1) the school building and materials; 2) the teacher; and, 3) what your children are learning in school? These questions were coded either “yes” or “no”. We summed the number of items to which the the respondent answered “yes” and created an index that captures satisfaction with schools. We also include a measure of how long it takes for respondents’ children to travel to school.

# **Local Councils’ Honesty, Competence and Capacity**

Respondents were asked the following hypothetical question that taps their perceptions of the honesty of local government officials: a) If the local council “was given 500 million Leones to complete a project in this area
**Can Labor Market Imperfections Explain Changes in the Inverse Farm Size–Productivity Relationship?**

# **Longitudinal Evidence from Rural India**

Klaus Deininger<sup>_1_</sup> , Songqing Jin<sup>_2_</sup> , Yanyan Liu3, Sudhir K Singh<sup>_1_</sup> _1World Bank_ _2Michigan State University_ _3International Food Policy Research Institute_ JEL Codes: J20, J21, J22, J23, J24, Q10, Q11, Q12

**Keywords: Agricultural -productivity; labor markets; India; Structural transformation for growth**
region (Bulgaria, Latvia, Lithuania, Macedonia, Poland, Romania and Turkey), two counties in East Asia (Indonesia and the Philippines), two countries in Middle East and North Africa countries (Egypt and Jordan) and South Africa. Countries differ in terms of the indicators collected, span and frequency of data, and coverage of rural areas: ECA countries do not report hours and earnings, and include only the means of key variables by demographic cell rather than individual workers’ outcomes; three LAC countries (Argentina, Brazil, and Chile) cover only urban areas; and earnings are often reported for salaried workers (Chile, and Indonesia). The size of the shock is measured as a change in GDP growth rates, and varies widely, from 1.7 percentage points in Indonesia

> 9 See Fallon and Lucas (2002).

> 10 In particular, exchange rates have changed relatively little during this crisis, while both Argentina and Indonesia experienced extraordinary currency devaluations during their crises.

> 11 For European countries, we use Eurostat Survey data instead of individual country’s Labor Force Survey, which were not available. Eurostat provides the mean of key labor market indicators by demographic cells. For European countries, age, education, and gender estimates rely on data from the 8 cells defined by the three characteristics, while urban/rural estimates rely on a separate set of 8 cells defined by residence, age, and gender.

7
the pension of individuals who have contributed at least 1,150 weeks, who are 62 years old if they are men or 57 if they are women and who do not have other income above the minimum wage. The FGPM is financed with a percentage of the contributions made by high-income subscribers. If these requirements are not met, the person receives their savings with their respective financial yields.

An important limitation of the main source of information used in the CEQ exercise (i.e., ENPH) is the inability to identify the type of pension scheme to which each person belongs. Given the low proportion of people in the RAIS, it was considered appropriate to carry out the calculations assuming that all pensioners belong to the RPM. Thus, panel A of Figure 1 shows the percentage of people making contributions to the pension system by income decile and panel B shows the percentage of people of pensionable age (i.e., older than 57 years if female and older than 62 years for men) who receive pension by income decile.

<!-- Start of picture text --> Figure 1. People that made contributions and pensioners among income deciles<br>Panel A: Percentage of the population that makes Panel B: Percentage of the population of pensionable<br>contributions to the pension system by decile age that receives pensions by decile<br>100 100<br>80 80<br>60 60<br>40 40<br>20 20<br>0<br>0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Decile Decile<br>Source: World Bank Group staff estimates based on the 2017 ENPH<br>Note: The deciles were put together using market income + per-capita pensions<br>population<br>% pensionable-age<br>% working-age population<br><!-- End of picture text --> As stated above,
their internal resources. Under the redistribution view of trade credit, firms with better access to external finance redistribute the credit they receive to less advantaged firms (Meltzer 1960; Nilsen 2002). For example, in the U.S. context Petersen and Rajan (1997) argue that firm age and size, strong correlates of trade credit extension in their sample of small U.S. firms, are also proxies for firms’ access to external finance. And their comparison with the larger U.S. firms covered in the Compustat dataset (which had better access to external finance than the NSSBF firms), shows that small firms are much less likely to extend trade credit.<sup>2</sup> In the Chinese context, Cull, Xu, and Zhu (2009) show that unprofitable SOEs were more likely to extend trade credit to their customers, many of which were already in arrears, than other SOEs and private firms. Regardless of performance, the SOEs

> 2 The average ratio of accounts receivable to sales for firms in the NSSBF sample was 7.3% compared to 18.5% for Compustat firms (Petersen and Rajan, 1997, pp.669-670).

9
# **1. Background and Introduction**

Integrated water resource management (IWRM) and organizing it primarily at the river basin level are two of the most common and widely repeated recommendations in the water resources literature of the last decade if not longer (Allee 1988; Galloway 1997; McDonald and Kay 1988; World Bank 1993). Basin management is often associated with the concept of decentralization, of managing water resources at the “lowest appropriate level.” (See, e.g., International Conference on Water and the Environment 1992; Mody 2001). Several conceptual arguments have been presented in favor of decentralization in water resource management, and basin-level management in particular: that the whole array of resources and use patterns in the basin will be taken into account, public participation will be greater and broader, management decisions will be based on better knowledge of local conditions, and so on.

Empirical studies of river basin management systems provide opportunities to examine the claims made for basin-level integrated resources management, and to explore factors that appear to influence its implementation and outcomes. In this research project, with the support of the World Bank, the project team has searched for those factors and their relationships to river basin management in two ways: with a survey of river basin organizations throughout the world, and with case studies of eight river basins analyzed in greater detail. Some of those eight cases involve relatively new basin organizations such as the Regional Water Management Authority in the Warta River basin in Poland and the Coordinating Commission for the Rio Grande de Tarcoles in Costa Rica. Others, such as the Guadalquivir river basin in Spain and the MurrayDarling river basin in Australia, have long histories.

Spain has perhaps the longest history of any country in developing formal governmental authorities on the river basin scale, with the earliest ones dating from 1926. Although the river basin authorities in Spain ( _confederaciones hidrograficas_ , or CHs) have experienced many changes that have reduced and expanded their responsibilities and their participatory structures over the ensuing 75 or more
prior to school entry: Results from the NICHD Study of Early Child Care. _American Educational Research Journal_ , _39_ (1), 133–164.

- Oreopoulos, P., Page, M. E., & Stevens, A. H. (2006). The intergenerational effects of compulsory schooling. _Journal of Labor Economics_ , _24_ (4), 729–760.

- Paterson, G., & Sanson, A. (1999). The association of behavioural adjustment to temperament, parenting and family characteristics among 5-year-old children. _Social Development_ , _8_ (3), 293–309.

- Pettit, G. S., & Bates, J. E. (1989). Family interaction patterns and children’s behavior problems from infancy to 4 years. _Developmental Psychology_ , _25_ (3), 413.

- Pradhan, M., Brinkman, S. A., Beatty, A., Maika, A., Satriawan, E., de Ree, J., & Hasan, A. (2013). Evaluating a community-based early childhood education and development program in Indonesia: Study protocol for a pragmatic cluster randomized controlled trial with supplementary matched control group. _Trials_ , _14_ (1), 259.

- Putnick, D. L., Bornstein, M. H., Lansford, J. E., Chang, L., Deater-Deckard, K., Di Giunta, L., . .. others (2012). Agreement in mother and father acceptance-rejection, warmth, and hostility/rejection/neglect of children across nine countries. _Cross-Cultural Research_ , _46_ (3), 191–223.

- Schady, N., Galiani, S., & Souza, A. P. (2006). Early childhood development in Latin America and the Caribbean. _Econom ́ıa_ , _6_ (2), 185–225.

- Smith, M. (2011). Measures for assessing parenting in research and practice. _Child and
use GDP per capita in constant 2011 international dollars adjusted for purchasing power parity. The CO2 emissions estimates retrieved from WDI were produced by the U.S. Department of Energy’s Carbon Dioxide Information Analysis Center (CDIAC), and include anthropogenic emissions from fossil fuel consumption and world cement manufacturing.

# **3.5 Missing values and outliers**

Forest cover loss included two outliers of respectively a 10.8% and a 5.4% loss in Namibia (2001, and 2005), for comparison the median observation across time in this country was 1.7%, we have capped these numbers at 3% which, seemed an appropriate maximum for the range of forest loss after inspecting a kernel density. We applied a 3 period simple moving average to further smoothen outliers. Our final dataset includes the losses for countries that held 72% of forest cover in 2000. The largest missing forest patch is that of the Russian Federation.

The WDI dataset contains a wealth of information, but some important observations are missing. GDP has only _._ 12% missing, manufacturing and services GDP shares have 5 _._ 57% missing. We interpolate these values by taking a weighted average of the nearest observations in the time dimension. The dataset includes approximately 83% of global carbon emissions and should be quite representative of missing countries as it is close to the 85% of world population included in our samples.

The WDI does not report income shares in each country but sometimes reports a Gini index. We used this to back out income shares.<sup>12</sup> After using both the Gini and reported shares, 61 _._ 25% of the observations remain missing, but missingness is only over the time dimension. In the countries that have more observations in the time dimension we observe that the income shares are relatively stable over time. We interpolate the remaining missing values using weighted averages of the nearest observations in the time dimension.

Poverty rates has 69
)|(0.015)|(0.029)|(0.029)|
|**R-squared**|0.09|0.091|0.122|0.123|0.559|0.561|
|**Number of observations**|84,724|84,724|49,348|49,348|34,585|34,585|

_Source:_ Authors’ calculationsbased on Cambodia Socio-Economic Surveys and the Sri Lankan 2002 and 2006 Household Income and Expenditure Surveys and the 2002 and 2008 Labor Force Surveys _Note:_ Standard errors in parentheses. Additional controls include age, age squared, marital status, education, industry, and occupation dummies.T&G = textiles and garments; MFA = Multi-fibre Arrangement. *** _p_ <0.01, ** _p_ <0.05, * _p_ <0.1.

We measure working conditions as an average of two dummies—a dummy for a worker above age of 14, and a dummy for a workweek that is less than or equal to a 40hours (see table 5, columns 1–4). We have to use such a narrow measure of working conditions due to the lack of a more comprehensive measurement in the data. Thus, a reader should keep in mind that this measure of working conditions reflects only two specific aspects of the job quality. In both cases, regressions are pooled across different survey years.

The results show that the working condition index in the Cambodian textile and garment industry deteriorated post-MFA by 5.2 percent, compared to other industries (table 5, column 1). Even though the post-MFA changes in female working conditions relative to male working conditions and compared to other industries are positive (see table 5, column 2), they are not significant, suggesting that women’s working conditions were not affected differently than those of men as a result of the MFA phase-out. These findings arenot far from the
that the results are not very sensitive to the procedure of selection of workers who formalize (randomly selected individuals in our static scenarios and individuals with the highest probability of informal employment according to the behavioral models). Therefore, the behavioral model confirms the robustness of the results of static simulations.

**Table 7: Simulated changes in indicators of income distribution and fiscal budget, behavioral simulation**

||no random component (1%<br>formalization)|with random component<br>(6.2%formalization)|
|---|---|---|
|Income of 1st decile, %|0.8|0.7|
|Income of the formalized, %||-11.7|
|Income total, %|0.9|0.8|
|Absolute poverty rate of the formalized, p.p.|0.0|9.3|
|Absolute poverty rate, p.p.|-0.2|-0.1|
|Gini index, p.p.|0.0|0.0|
|Total budget balance, %ofGDP|-0.6|-0.5|

Source: Authors’ calculations using RUSMOD for 2017 policy year and 2016 RLMS-HSE data.

If the economic incidence of SIC falls on workers, all deciles and age groups benefit from the tax maneuver and the formalization that it drives. As shown in Figure 11, on average, per capita household consumable income increases by 0.8 percent. The highest gain goes to the 8th and 9th decile – they get an additional 1.3-1.4 percent of consumable income, while the lowest effect is observed in the middle of the income distribution (0.4 percent for the 5th decile) and at the top (0.5 percent for the 10th decile). The reform has the highest positive welfare impact for families with working age adults and with 1-2 children. Families with
# **Appendix B: VAR-based impulse response results for Malaysia and Singapore**

# **B1. Estimation framework and data**

For comparison, the impact of a US policy interest rate shock on two non-dollarized economies in the Southeast Asian region, Malaysia and Singapore, is examined. This is done by investigating VAR-based impulse responses of the variables under consideration with respect to a change in the US policy interest rate.

Variables included in the VAR model are the same as the estimation for the Cambodian case. Specifically, they include the US federal fund rate ( _ffr_ ), the growth rate of domestic currency to USD exchange rate ( _z_ ), the trade balances with the EU ( _tbeugdp_ ) and with the US ( _tbusagdp_ ), money balance as a share of GDP ( _bmgdp_ ), domestic interest rate ( _domint_ ), output gap ( _gygap_ ), and consumer price index (CPI) inflation ( _infl_ ). Output gap is the difference between real GDP and real potential GDP (i.e. GDP under full employment), scaled by real potential GDP. Potential GDP in real values for the calculation of output gap data is generated by applying the Hodrick-Prescott filter on the real GDP data. Furthermore, the fluctuation of the crude oil price represented by its change rate ( _goilp_ ) and a dummy variable ( _dummy_ ) are exogenously included in the VAR system as a control for external shocks. The dummy variable is included to reflect effects resulting from the 1997-98 Asian financial crisis and the 2008-2009 global financial crisis. Like the Cambodian case, quarterly data are considered for the estimation. Due to the availability of data for domestic interest rate, the sample period for Malaysia is from 1994Q4 to 2015Q3 and for Singapore is from 1994Q4 to 2013Q2. The data for US federal fund rate, domestic currency to USD exchange rate, broad money (M2, a proxy for money balance), domestic interest rate,<sup>19</sup> GDP, and CPI are obtained from the International Financial
principals may be investing more in earlier grades driven by a belief that learning delays emerge early in the life of the child. Indeed such a belief is actively promoted by PASEC.

Using data from the teachers' questionnaires at follow-up we investigate whether there were dierential impacts of school grants on observable investments in 3<sup>_rd_</sup> and 5<sup>_th_</sup> grade students in Panel A of Appendix Table 9.<sup>14</sup> Some of the variables we can study are classroom materials (e.g., textbooks/manuals, desks, tables, etc), and teacher training. We nd no dierential impact of the program in any of these. When we examine other classroom characteristics or teacher behaviors, the only interesting dierence to report concerns student (mis-)behavior in the classroom. While in third grade there was a positive impact of the program on student behavior as measured by the number of times a day a teacher needs to demand silence, in fth grade there was a negative impact of the program on student behavior measured by this variable, and by the number of times a teacher has to punish a child for impolite behavior.

Observable parental investments are not dierent between grades three and ve (see Panel B of Appendix Table 9), which is prima facie evidence that the dierences are attributable to the eectiveness or administration of grants between the grades.

# 5.2 Distributional Impacts

Whether the program has dierent eects across the distribution is an important question relating to targeting. In Figure 3 we show parameter estimates together with their 95% condence intervals from a quantile regression of the relevant test scores for grade three in the rst follow-up (rst column) and second follow-up (second column), on the treatment indicator and including the usual controls, clustered by school. The eects of the grant are generally spread over most of the
23 His focus does not extend, however, the institutional and informational conditions that made such interactions possible.

# Data

The three hypotheses outlined earlier require information on the benefits to special interests of regulatory decisions of government in the financial sector, the potential costs to society of those benefits, the completeness of voter information on the actions of political actors, and the political institutions in which political actors are making these decisions. The assembly of such a set of variables is a challenging proposition, but a number of reasonable variables are available in each of these categories. These indicators, the institutional and informational variables, and other control variables used in the analysis are described here.

# Financial sector

Three financial sector variables are crucial to the analysis. Fiscal transfers and forbearance, the dependent variables identified earlier, are taken from Honohan and Klingebiel (1999). The third variable captures the costs of crisis to voters, found in Result 5 to play a key role in the analysis.

Honohan and Klingebiel (1999) have assembled data on government responses to financial crisis for 40 crises in 35 countries.22. In particular, they have calculated the magnitude of fiscal transfers governments made in response to crisis and they have tracked whether governments exercised forbearance in their oversight of insolvent banks. Their calculations of fiscal transfers include both the fiscal and quasi-fiscal outlays for financial system restructuring, including the recapitalization cost for banks and the costs of indemnifying depositors. Transfers range from 0.5 to 55.1 percent of GDP.

22 They relied on Caprio and Klingebiel (1997 and 1999) and Lindgren, Garcia and Saal (1996), resolving conflicts by consulting with country experts.