rafmacalaba/datause-encoder-data huggingface dataset:
From the point of view of the present discussion, it is notable that the NSS series does not reflect fully the gains in mean consumption indicated by the NAS from the early 1990s onwards. Upon regressing consumption growth from the NSS on that from the NAS, with controls for changes in whether the round used MRP and changes in the log ratio of rural price index to the National Accounts deflator, the overall elasticity of the NSS mean consumption to NAS consumption is 0.48 (t=4.03). The elasticity is significantly less than unity. The elasticity is also lower in the post-1991 period, declining to 0.45 (t=3.29) from 0.57 (4.47) in the pre-1991 period. However, one cannot reject the null hypothesis that the elasticities for the two sub-periods are the same. To investigate further the source of divergence between NAS and NSS consumption in the two sub-periods, we also regressed the difference between NAS and NSS mean consumption growth rates on dummy variables for pre-1991 and post-1991 sub-periods, and on pre- and post-1991 per capita net domestic product (NDP) growth rates. (All regressions include controls for change in dummy variable for an MRP round as well as change in the log ratio of rural price index to the NA deflator.) These tests confirmed that the divergence in the NAS and NSS mean consumption growth rates has been greater in the post-1991 period, although the difference between the two sub-periods is not statistically significant. We also found that the divergence between NAS and NSS mean consumption growth rates tends to be higher the higher the per capita NDP growth rate, and this association between NAS-NSS divergence and per capita income growth is somewhat stronger in the post-1991 period.

We do not know what role NSS survey methods have played in this divergence from NAS consumption. By international standards, the NSSO’s methods appear to have changed rather little over many decades. That is probably good news for comparability reasons, although it does raise questions about whether their methods are in accord with international best practice. This is something that should be reviewed in the future, in the light of international experience. However, it is notable that the MRP rounds of the NSS have helped close the gap between the NAS and NSS consumption aggregates. Regressing the log difference of the NSS mean on the log difference of NAS consumption and the change in the dummy variable for MRP rounds, the latter variable has a coefficient of 0.055 (t=4.14). This suggests that NSS design may account for at least some of the discrepancy between the two data sources.

14
report that it was useful for their daily work (7 _._ 8 _pp_ for 5<sup>_th_</sup> grades and 12 _pp_ for 9<sup>_th_</sup> grades).

Next, we analyse textbook quality and distribution. Using the SAEB questionnaire of principals, the estimates indicate that schools in _Ceará_ are 10 _pp_ to 25 _pp_ less likely to report a lack of textbooks than similar principals on the other side of the border. This reduction only occurs after TA is introduced. At the same time, 5<sup>_th_</sup> grade teachers in _Ceará_ report that textbooks are at least “ ” “ ” _good_ or _great_ around 9 _._ 5 _pp_ more frequently than their counterparts. Considering concerns raised in previous literature regarding the impacts of textbooks on learning (Glewwe et al. 2009), note that the state of _Ceará_ structured these textbooks to support over-age students. Thus, the distribution of good quality textbooks to municipal schools is argued to be a mechanism explaining our findings.

The last group of mechanisms analyzed is related to pedagogical practices. During “RBF+TA” periods, 5<sup>_th_</sup> grade students in _Ceará_ became 2 _pp_ more likely to report that their teachers checked their homework (in both mathematics and Portuguese) than students studying in schools located in the circumventing municipalities outside of _Ceará_ . For 9<sup>_th_</sup> grades no significant result was found for this particular outcomes. Importantly, teachers in _Ceará_ were around 8 _pp_ more likely to cover at least 80% of the school curriculum for both grades, and 11 _._ 6 _pp_ for 9<sup>_th_</sup> grades teachers, after the RBF rule was reformulated in 2013.

We also show evidence that the introduction of the RBF increased public spending on education per pupil by 1 _._ 2% relative to the baseline mean in the municipalities of _Ceará_ when compared to municipalities across the border. The introduction of RBF led mayors to invest in school facilities (e.g., internet connections, computer labs, libraries, and sports courts). Moreover, the increase in public spending per capita on complementary public services is even larger, varying from 10 _._ 5% to 21% depending on the type of service. In contrast, the introduction of TA jointly with the RBF and the reformulation of the RBF mechanism did not translate into more education spending in 5
Michael J. Harper (Eds), _New Developments in Productivity Analysis_ . Chicago: University of Chicago Press.

- Gollin, Douglas, Stephen L. Parente, and Richard Rogerson. 2004. “Farm Work, Home Work, and International Productivity Differences,” _Review of Economic Dynamics_ (7): 827-850.

- Griliches, Zvi and Haim Regev. 1995. “Firm Productivity in Israeli Industry: 1979-1988 _.” Journal of Econometrics_ 65: 175-203.

- Gunner, Nezih, Gustavo, Ventura, and Yi Xu. 2008. “Macroeconomic Implications of SizeDependent Policies,” Review of Economic Dynamics 11(4): 721-744.

- Haltiwanger, John. 2015. “Job Creation, Job Destruction, and Productivity Growth: The Role of Young Businesses,” _Annual Review of Economics_ 7: 341-358.

- Hopenhayn, Hugo. 1992. “Entry, Exit, and Firm Dynamics in Long run Equilibrium,” _Econometrica_ 60(5): 1127-1150.

- Hopenhayn, Hugo. 2014. “Firms, Misallocation, and Aggregate Productivity: A Review,” Annual Review of Economics 6: 735-770.

- Hopenhayn, Hugo and Richard Rogerson. 1993. “Job Turnover and Policy Evaluation: A General Equilibrium Analysis,” _Journal of Political Economy_ 101(5): 915-938.

- Hsieh, Chang-Tai and Peter J. Klenow. 2014. “The Life Cycle of Plants in India and Mexico,” _Quarterly Journal of Economics_ 129(3): 1035-1084.

- Jovanovic, Boyan. 1982. “Selection and the Evolution of Industry,” _Econometrica_ 50(3):649-670.

- Jones, Patricia, Taye Mengistae, and Albert Zeufack. 2018. “Selection, Firm Turnover, and Productivity Growth,” World Bank Policy Research Working Paper 8291.

- Kalemli-Ozcan, Sebnem and Bent E. Sorenson. 2012. “Misallocation, Property Rights, and Access to Finance: Evidence from Within and Across Africa.” NBER Working Paper 18030.

- Levinsohn, James and Amil Petrin. 2003. “Estimating Production Functions using Inputs to Control for Unobservables,” _Review of Economic Studies_ 70(2): 317-341.

- Melitz, Marc J. “The Impact of Trade on Intra-industry Reallocations and Aggregate Industry Productivity,” _Econometrica_ 70(6): 1695-1725.

- Melitz, Marc J. and G.I.P. Ottaviano. 2008. “Market Size, Trade and Productivity”, _Review of Economic Studies_ 75: 295-316.

- Melitz, Marc J. and G.I.P. Ottaviano. 2008. “Market Size, Trade and Productivity”, _Review of Economic Studies_ 75: 295-316.

21
23

# F) What the previolis grnwth regreccions really show

There are two empirical findings from the growth literature that appear to contradict the present results: growth regressions using enrollment rates and growth regressions in which the growth of output is specified as a function of the level of schooling.

# 1) Growth and enrollment ratec

A huge literature exists showing that enrollment rates are robustly correlated with growth rates (Barro, 1991, Levine and Renelt, 1992). The justification for putting enrollment rates into growth regression has typically been a more or less explicit argument that the enrollment rates are a proxy for the flow of investment in human capital which is a proxy for the change of the stock of human capital of the labor force (Mankiw, Romer, Weil, 1992)3'. However, the enrollment rate is a valid proxy for the rate of accumulation of schooling across countries only if each country is roughly at their steady state rates of the stock and the enrollment rates are constant over time across countries<sup>38</sup> . This assumption is obviously false as it ignores what is one of the most well known and striking features about development. the massive expansion of schooling (Schultz, 1988). This false assumption works to make initial enrollment rates a worse than terrible proxy for the rate of growth of human capital, as the correlation between either of the estimates of the actual growth of the stock since 1960 and the primary or secondary enrollment rates in 1960 is strong and negative (table 7). A terrible proxy would be at least uncorrelated.

**37** I argue that MRW were roughly right about what the humnan capital share 'ought" to be, about .33 (in their paper they suggest a share of .33 for each of physical capital, humnan capital, and labor). However, I disagree sharply that the aggregate data can be used to support an estimate of .33.

**38** This waring about levels of investnent and changes in stocks holds true for physical capitl as well. The correlation between the investment share and the growth of capital stocks is very near zero (Pritchett, 1995).
Singapore: Includes "retirement and related" withdrawals, "other" withdrawals, social assistance spending and estimated spending on public employees' schemes based on assumption of constant real spending between 1986 and 1989. Housing and Medisave withdrawals excluded.

Spain: Includes compulsory schemes from local and central government employees and redundancy benefits from Eurostat 1992a. Figure reflects revisions to GDP since publication.

Swaziland: Assumes constant real spending on public employees' schemes between 1983 and 1986. New figure uses weighted average of 1985 and 1986 GDP to correspond to fiscal year reporting.

Sweden: Includes "basic", "supplementary" and "additional" pensions of the old age, anticipatory, special anticipatory and survivors' branches.

Switzerland: Includes AVS, AI and PC at the national as well as the cantonal level. The difference from original figure reflects the use of IMF GDP figures instead of preliminary estimates made by the Swiss ASS in their publication.

Tanzania: Assumes that real spending on special schemes for public employees remained constant between 1986 and 1990. GDP is weighted average of 1990 and 1991 GDP to correspond to fiscal year reporting.

Trinidad and Tobago: Includes National Insurance, the non-contributory pension, and estimated spending on public employees' schemes based on assumption of constant ratio of other pension spending to this category between 1983 and 1989. GDP is weighted average to correspond to fiscal year reporting.

Tunisia: Includes CREGT, CAVIS and CNRPS, Table 2, Vittas 1993.

Ukraine: New figure based on different source considered more reliable.

United Kingdom: GDP based on weighted average to correspond to fiscal year reporting.

United States: Includes OASDI, railroad, and public employees' retirement (including military) and Supplemental Security Income (SSI). Data excludes pension spending by States on their own retired employees.

Uruguay: Reflects revised GDP figures since publication. Does not include banking, military pensions.

Venezuela: Includes IVSS, non-contributory pensions within ministries, military, university and state enterprise pensions as well as means-tested pensions from INAGER (Instituto Nacional de Gerentologia). Excludes pensions of PDVSA (state oil company). Isuani (1991) is the source for all non-IVSS spending data.

Relationship between Pension and Health Spending, Population Aging and Income per Capita. Figures 1.8, 1.9 and 1.10 present evidence on the relationship between pension spending and population aging and income per capita, where pension spending is normalized by national income. Note that pension spending does not include tax expenditures. Inclusion of these expenditures in the dependent variable for countries like the U.S., the U.K. and Australia for which data are available seems to improve the fit generated by the regression in Figure 1.8, suggesting possible substitutability between public and private spending. The regression results imply that demographic aging is a better predictor of the pension spending 12
Policy ReseaRch WoRking PaPeR 4908

# **Abstract**

The contribution of return migrants to economic development in source countries can be significant. Overseas savings of returnees may lead to improvements in household welfare and provide liquidity for investments in the face of credit market failures. Labor market experience and skills acquired abroad may also lead migrants to find occupations higher in the skill and remuneration spectrum upon return. This study uses the 2005 Albanian Living Standards Measurement Study Survey and estimates the impact of international migration experience on the occupational mobility of return migrants vis a vis working-age Albanian residents that never migrated. Controlling for the non-random nature of international migration and return, the results show that past migration experience increases the likelihood of upward occupational mobility. Exploring the heterogeneity of impact by host country indicates that the positive effect of past migration experience on upward occupational mobility is driven by past migration experience in Italy and countries further a field, while past migration experience in Greece does not exert any significant impact on mobility outcomes. The results, which are consistent across different sample specifications and outcome variables measuring occupational mobility, hint at the link between migration and human/financial capital formation among migrants and foster optimism concerning the positive effect of return migration on economic development. This insight is particularly important since remittances from permanent migrants, which have fueled the impressive growth performance of the country in the recent era, may taper off in the medium to long term with the decline in out-migration and growing global economic woes.

This paper—a product of the Poverty Team, Development Research Group—is part of a larger effort in the department to study the impact of migration on poverty and other outcomes in source countries. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at gcarletto@worldbank.org and tkilic@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
cheaper or administratively easier for local businesses to start and run operations; or a reform that defines and increases the protection of property rights. An example is reducing the number of days to get an industry license, eliminating the minimum capital requirement for start-ups, or increasing the legal rights of creditors and minority shareholders.

Using this dataset, we define the main dependent variable, _Reform_ , as a dummy variable equal to 1 if a positive reform occurred in one or more of the ten indicators in a given year and 0 otherwise. The mean value of the variable equals 0.55 and the standard deviation is 0.50 (Table 2). For robustness, we also report all results using an alternative measure that equals (log of 1 plus) the number of indicators on which a positive reform occurred during a given year ( _Number of Reforms_ ). For example, in 2005, Turkey implemented reforms in paying taxes and international trade implying a score of (log of 1 plus) 2 for the dependent variable. The two dependent variables are highly correlated (correlation of 0.877).

Information on changes in the quality of the business environment is also available from alternative sources such as Heritage Foundation’s Freedom of the World Index or Fraser Institute’s Economic Freedom of the World. One could use annual changes in these data to construct a measure of reform similar to the ones described above. However, the Doing Business data offer two advantages. First, unlike other data sources that are based in part on experts’ perceptions, the Doing Business data are based on actual reforms. This allows us to interpret the findings in terms of specific reforms that are more (or less) likely under a democratic vs. non-democratic environment. Second, and more important, since the Doing Business data cover a specific set of policy reforms, 6
# **1. Introduction**

In parts of Asia, South Caucasus, and the Balkans, son preference is strong enough to trigger substantial levels of prenatal and postnatal sex selection, result in the excess mortality of girls, and skew child sex ratios in favor of boys (see Figure 1). Every year, an estimated 1.8 million girls under the age of five go “missing” because of sex selective practices widely adopted in these regions (The World Bank 2012).<sup>3</sup> This is almost as if the entire female population of Los Angeles, California, vanishes annually.

Figure 1: Child sex ratios for select regions and countries, 2010-15 <!-- Start of picture text --> SUB-SAHARAN AFRICA<br>NORTHERN AMERICA<br>EUROPE<br>Pakistan<br>Georgia<br>India<br>Vietnam<br>Armenia<br>Azerbaijan<br>China<br>1.00 1.02 1.04 1.06 1.08 1.10 1.12 1.14 1.16<br><!-- End of picture text --> Notes: Child sex ratio: boys/girls, < 5 years of age Figure 1 displays child sex ratios for countries where the ratio is greater than 1.06. 1.06 is used as a cutoff to restrict this figure to countries where the ratio of boys to girls is strikingly skewed. Normal child sex ratios, i.e. when there is no prenatal and postnatal sex selection, would be 1.00 or close to 1.00. Normal sex ratios at birth (SRB), i.e. when there is no prenatal sex selection, would be 1.06.

South Korea is not included here because it has seen a turnaround in its' sex ratio since the mid-1990s Source: United Nations (2017) While excess girl mortality has been documented in countries like China; Taiwan, China; India; and Pakistan since the early twentieth century (Visaria 1971; DasGupta & Li 1999), it is a more recent phenomenon in countries like Albania, Armenia, Azerbaijan, Georgia, Vietnam, and Nepal. In Albania, it has been noted since the 1970s. In the South Caucasus, it has been noted since the 1990s, following the collapse of the Soviet Union. In Vietnam and Nepal, it has been noted since

> 3 Across all regions in the world, 2.04 million girls go “missing” annually.

2
20 to vary across developed and developing countries we find all of the negative effect on economic performance is in the OECD counties, where the effect of labor force growth is strongly negative and significant<sup>23</sup> . On the other hand the estimated effect in the developing countries is positive, .15, (although insignificant). This seems to imply that the slope of the economic growth-population growth relationship depends is noE constant but that, contrary to intuition, labor force growth is worse for the richer industrialized than developing countries.

Table 3: Partial Correlation of Labor Force **Growth with** Growth Rate of **Output** per Worker, 1960-1990. Smiple divided by regions.

|Control<br>variables:|None|YO|YO,BMP,LLY,XS||
|---|---|---|---|---|
|All|-.10<br>(.37)|-.12<br>(.28)|0.04<br>(.73)|79|
|OECD|_-.50_<br>(.02)|-.08<br>_(01)_|-.04<br>(.89)|22|
|Developing<br>l__________|0.15<br>(.25)|0.16<br>(.24)|0.10<br>(.48)|_56_|
|Africa<br>l__________|-.01<br>(.98)|0.02<br>(.93)|-.09<br>(.73)|19|
|Latin<br>America|0.32<br>(.20)|0.33<br>(.19)|0.50<br>(.07)|18|
|Asia/<br>Pacific|0.60<br>(.04)|0.66<br>(.03)|0.75<br>(.03)|12|

Notes: p-levels of the test for zero correlation are in parenthesis.

23 This result is the same as Maniiw, Romer, Weil find with the estimated mpat higher and stascally significant in the OECD (-.21) while smaller (-.14) in LDCs.
A Duration Analysis of CONALEP

# **Table 5.  Kaplan-Meier Estimates Job Search after graduation from CONALEP (Months)**

||Time Es<br>|timated<br>|
|---|---|---|
|_Probability {T>t}_|_Survey 94_|_Survey 98_|
|0.25|12.0|7.0|
|0.5|4.0|3.0|
|0.75|1.6|1.0|
|Mean|9.2|6.8|
|Median|4.0|3.0|
|Cases censored|169 (20.4%)|124 (3.8%)|
|Total number of cases|827|3273|

Table A1.1 shows the hazard ratio or risk of finding a job in a respondent’s region. Graduates from the 98 Survey have a 45 percent greater probability of finding a job than graduates from the 94 Survey do. Graduates from the northern or central regions of Mexico have a higher probability of finding a job (between 60 and 45 percent) than graduates from the South (22 percent) do. The 1993-1996 cohort had a 4 percent higher probability of finding a job than the other cohorts did. Also, the higher the level of schooling of the household head, the higher the chance the CONALEP graduate had of finding a job.

In Table 6, various scenarios were calculated. Given a base category (male, living in the central region, age, and so on.), the median time for a male graduate to find a job in the 94 Survey is 4 months, and in the 98 Survey—2.8 months. The mean length of time that female graduates search for a job is longer than that for male graduates. Furthermore, female graduates in the 98 Survey found jobs faster than those from the 94 Survey did. Not surprisingly, the job search is longer for graduates who did not have any job experience while studying. However, the difference in job search time between individuals with work experience and those without is small.

Given the above base category, 18 percent more of 98 Survey respondents than those in the 94 Survey were working (see Table 7). In the 94 Survey, the North, Center, and Pacific regions correlate with an increased probability of working. The probability of searching for a job is 17 percent higher for the 1994 graduates than it is for the 1998 graduates. For 1994 female 14