rafmacalaba/datause-encoder-data huggingface dataset:
Dex, Shirley, Gustafsson, Siv, Smith, Nina, and Tim Callahan. 1995. “Cross-National Comparisons of the Labor Force Participation of Women Married to Unemployed Men,” _Oxford Economic Papers_ 47(4): 611-635.

Do, Quy-Toan, and Lakshmi Iyer. 2010. “Geography, Poverty and Conflict in Nepal,” _Journal of Peace Research_ , forthcoming.

Finegan, T. Aldrich, and Robert A. Margo. 1994. “Work Relief and the Labor Force Participation of Married Women in 1940,” _Journal of Economic History_ 54 (1): 64-84.

Ghani, Ejaz, and Lakshmi Iyer. 2010. “Conflict and Development – Lessons from South Asia,” _Economic Premise_ 31: 1-8.

Gujarati, Damodar N. 2003. _Basic Econometrics_ . Fourth edition. New York: McGraw-Hill.

Ibáñez, Ana María, and Carlos Vélez. 2008. “Civil Conflict and Forced Migration: The Micro Determinants and Welfare Losses of Displacement in Colombia,” _World Development_ 36 (4): 659-76.

Informal Sector Service Center (INSEC). 2010. “No. of Victims Killed by State and Maoist in Connection with the „People's War‟ Database.” On-line Database. Available at http://www.insec.org.np.

Jones, Nicola, Holmes, Rebecca, Marsden, Hannah, Mitra, Shreya, and David Walker. 2009. “Gender and Social Protection in Asia: What Does the Crisis Change?” Background Paper for Conference on the Impact of the Global Economic Slowdown on Poverty and Sustainable Development in Asia and the Pacific, Overseas Development Institute.

Lokshin, Michael, and Elena Glinskaya. 2009. “The Effect of Male Migration on Employment Patterns of Women in Nepal,” _World Bank Economic Review_ 23 (3): 481-507.

29
**27**

enforcement is poor, values of ENFORCE less than **_5,_** include Colombia, Nigeria, Pakistan, Philippines, Peru, and Zimbabwe.

# **_3._** _Accounting standards_

Information about corporations is critical for exerting corporate governance and identifying the best investments. Accounting standards that simplify the interpretability and comparability of information across corporations will simplify financial contracting. Furthermore, financial contracts that use accounting measures to trigger particular actions can only be enforced if accounting measures are sufficiently clear. Accounting standards differ across countries and governments impose an assortment of regulations regarding information disclosure. Since accurate information about corporations may improve financial contracting and intermediation, the paper examines a measure of the quality of information disclosed through corporate accounts from LLSV **(1998).**

**ACCOUNT** is an index of the comprehensiveness of company reports. The maximum possible value is **90** and the minimum is **0.** The Center for International Financial Analysis and Research assessed general accounting information, income statements, balance sheets, funds _flow_ statement, accounting standards, and stock data in company reports in **1990.** We expect **ACCOUNT** to be positively correlated with financial intermediary development.2 As shown in Table **6, ACCOUNT** exhibits substantial cross-country variation. The maximum value is **83,** Sweden, while the minimum

> 2 This is not necessarily true and raises the need for a general conceptui qualification. An economy with perfect

> information, perfect contract enforcement and perfect legal codes (i.e., and economy with essentially zero transaction and information costs) would have little reason for financial intermediaries. Put differently, market frictions motivate the emergence of financial intermediaries, e.g., Boyd and Prescott **(1986).** Conceptually, this implies that at very high levels of legal system development and information dissemination, a marginal increase in legal efficiency or information quality may cause a _reduction_ in the role and importance of financial intermediaries. However, quadratic expressions for

> **ACCOUNT** and CONRISK never entered significantly.
<!-- Start of picture text --> Generalized Spearman corelation<br>0.24<br>0.22 :<br>é<br>: . ca ra<br>02 . , ‘ 7 va a<br>3 7 ~ \ ifs a<br>Oo i a an. or oe<br>a x fie<br>0.14 a “Tse Le SNE<br>0.12 lt a BF<br>0.1<br>1995 1996 1997 1998 1999 2000 2001 2002 2003<br><!-- End of picture text -->
Policy Research Working Paper 7246

# **Abstract**

Technical education and training has been dramatically expanding in Brazil recently. However, there remains no evidence on the cost effectiveness of this alternative track to a more general education. This paper quantifies the wage returns of completing technical and vocational education and training compared with the returns of completing the general education track, for individuals with similar observable characteristics. Exploring data from the Brazilian National Household Sample Survey, the paper profiles the students taking up this track and quantifies the impact of different types of technical and vocational education and training courses on individuals’ hourly wages. After controlling for selection on observables with propensity score

- matching, the analysis shows positive and statistically sig nificant wage premiums for students completing technical school at the upper secondary level (on average 9.7 percent ) and for those completing short-term training courses (2.2 percent on average). The paper also documents significant heterogeneity of impacts depending on the courses  and the profile of students. For realistic unitary costs of providing technical and vocational education and training, the evidence suggests technical education is a cost-effective modality. The courses offered by the publically financed and privately managed “Sistema S,” together with courses in the manufacturing area have the highest positive impacts.

This paper is a product of the Education Global Practice Group. It is part of a larger effort by the World Bank to provide 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://econ.worldbank.org. The authors may be contacted at ralmeida@ 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
# **3.1.3  ALMP Programs in China**

Bidani, Goh and O‟Leary (2002) analyze the effects of a retraining program in China called the “Reemployment Project,” which was designed to promote labor market entry of so-called _xiagang_ , people who were laid off from state-owned enterprises but remained attached to their former employer for unemployment stipends, health insurance, pensions and sometimes also housing. The Reemployment project was administered by labor bureaus in local areas and included a range of active labor market policies such as job search assistance, counseling, training, wage subsidies, tax incentives for firms and assistance for self-employment. Individuals were allowed to be registered with the Reemployment service for up to three years.

The impact evaluation study was carried out in a city with very high unemployment, Shenyang, in northeastern China, and in another city with moderate unemployment, Wuhan, in central China. The laid-off workers were 47% female, tended to be less educated and were concentrated in the <35, and 35-46 year-old range. The training intervention was relatively shortterm (one month, 132 hours of classroom training) and included courses in computer training, beauty and massage, hair cutting, sewing, toy making, cooking, repair training and driver education. Class sizes during the training sessions were often large with 200 to 300 workers in a small classroom.

Analysis samples were drawn from a census which required each state-owned enterprise to provide a list of workers laid off at different times. The sample of trainees was selected from the training registers from the training institutes (in the case of Shenyang) and from a master list supplied by the Wuhan Labor Bureau.<sup>11</sup> Three different treatment/comparison group samples are analyzed using multiple methodologies that include prop score matching, matching on odds ratios, and OLS. The outcomes of interest are employment and earnings, and, with a few exceptions, most of the impact estimates are robust to the use of different methods. Training is found to have had a negative impact in Shenyang on employment probability and no effect on earnings. In Wuhan, however, training is found to have had a positive impact on employment probability. The estimated impact on earnings is difficult to ascertain in the case of Wuhan, because the estimates are not robust to changes in the sample used for the analysis and/or estimator used.

> 11 No-shows were excluded from the treatment group and in some cases included in the control group and crossovers were excluded from the control group and in some cases added to the treatment group.

23
**Table 4. Parent Matchmaking, Love, and Money**

|||**Harmony**||**Log(c**|**ouple joint incom**|**e)**|
|---|---|---|---|---|---|---|
||**OLS**|**OLS**|**2SLS**|**OLS**|**OLS**|**2SLS**|
|rural|0.068|-0.015|0.083|0.011|-0.007|0.169**|
||(0.172)|(0.139)|(0.244)|(0.043)|(0.037)|(0.074)|
|parent matchmaker|-0.105**|-0.095**|-1.700**|-0.002|0.001|0.448**|
||(0.048)|(0.048)|(0.784)|(0.019)|(0.019)|(0.206)|
|parent matchmaker * rural|0.055|0.064|0.631|-0.043|-0.042|-0.865***|
||(0.060)|(0.060)|(0.787)|(0.031)|(0.031)|(0.232)|
|ln(age)|0.182**|0.132*|0.269**|0.174***|0.161***|0.184***|
||(0.088)|(0.080)|(0.107)|(0.039)|(0.038)|(0.048)|
|Schooling|0.003|0.002|-0.003|0.023***|0.022***|0.021***|
||(0.004)|(0.004)|(0.006)|(0.005)|(0.005)|(0.004)|
|Mother schooling|0.001|0.000|-0.000|-0.000|-0.001|0.000|
||(0.004)|(0.004)|(0.006)|(0.003)|(0.003)|(0.003)|
|Father schooling|-0.001|-0.001|-0.003|0.004*|0.004**|0.003|
||(0.004)|(0.004)|(0.005)|(0.002)|(0.002)|(0.002)|
|Communist Party|0.024|0.023|0.022|0.083***|0.083***|0.075***|
||(0.031)|(0.030)|(0.038)|(0.014)|(0.014)|(0.015)|
|Ln(township income per|0.051|0.045|0.014|0.973***|0.971***|0.956***|
|capita)|(0.037)|(0.034)|(0.033)|(0.010)|(0.010)|(0.012)|
|Avg township schooling|-0.008|-0.023|-0.043*|-0.006|-0.010|-0.017**|
||(0.032)|(0.023)|(0.024)|(0.007)|(0.007)|(0.008)|
|Religion, ethnicity dummies|No|Yes|Yes|No|Yes|Yes|
|Number of observations|6,050|6,050|6,050|6,334|6,334|6,334|
|Adjusted R2|0.005|0.015||0.845|0.846||
|Cragg-Donald Wald F stat|||31.6|||29.8|
|Kleibergen-PaapWalk rk F stat|||18.2|||16.9|

*, **, and ***: statistically significant at the 10, 5, and 1 percent level. White-corrected standard errors clustered at the township level  in parentheses

39
that enables us to examine how business practices relate to outcomes across countries, and to explore what determines differences in business practices among firms within each country.

Four of the surveys (in Ghana, Kenya, Nigeria and Sri Lanka) also provide panel data on the sampled firms. These allow us to examine survival rates over a one year horizon using data from 7,016 firms, and the stability of business practices over a one year horizon with data from 5,742 firms. The Sri Lankan data also provide a longer panel, enabling us to examine the relationship between business practices and subsequent survival over a 5.5 year period.

# **2.3 Summary Statistics**

Table 1 provides summary statistics for the full sample, and for each of the seven countries. In the combined sample, the median firm has zero employees and earns US$167 per month. 96.7 percent of the sample has nine or fewer workers. The gender distribution varies across countries, from the all-female samples in Kenya and Mexico, to a sample of 99 percent male owners in Bangladesh. The average business owner is 41 years of age and has 9.7 years of education; the average firm age is 8.7 years. Owners are youngest and most educated in the Nigerian sample, which comes from a youth business plan competition. Across all samples, most firms are informal, with only 34 percent in the combined sample reporting that they are registered for taxes. The businesses are a mix of trade, manufacturing and services, with this mix varying across the different countries.

# **2.4 Distribution of Business Practices**

Table 1 shows that on average firms in the samples employ 39 percent of the 26 business practices measured. The most frequently used practices are knowing which goods make the most profit per item (83%), not running out of stock frequently (70%), working out the cost of producing each main product sold (66%), and attempting to negotiate with suppliers for lower prices (58%). The least frequently used practices are preparing a balance sheet (5%), cash flow statement (7%), income and expenditure statement (16%), and doing advertising (17%). This is reflected in the four main subcomponents: the financial planning score is lower on average than the scores for other components. Table A4 reports means for the individual practices by country.

Figure 1 plots histograms of the distributions of business practice scores in each country. Recall that differences in the sample frames across countries make inter-country comparisons less 6
<!-- Start of picture text --> LHS\RHS ‘ RHS - Loan & Profit Component<br>4543 \ LHS - Deposit Component<br>: ‘ LHS - Income Lower 50%, . |...<br>at i‘‘S ILHS - Income Higher S0%_<br>3.5 .\<br>:\<br>3 4. ~ ~ .<br>.* ~ ~~<br>2.5 5.see ~<br>so<br>2 . weea ~<br>"., . wee ~.8 a<br>1.5 “ee, a Salata<br>0.5 tte eee eeeeeeeseesseesesecessensce<br>p<br>0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1<br>-0.5<br><!-- End of picture text -->

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# **Bibliography**

- Anderson, J. E. (2011, September). The Gravity Model. _Annual Review of Economics 3_ (1), 133–160.

- Berthélemy, J.-C., M. Beuran, and M. Maurel (2009). Aid and migration: Substitutes or complements? _World Development 37_ (10), 1589–1599.

- Bertoli, S. and J. Fernández-Huertas Moraga (2013). Multilateral resistance to migration. _Journal of Development Economics 102_ (C), 79–100.

- Bertoli, S. and J. Fernández-Huertas Moraga (2015). The size of the cliff at the border. _Regional Science and Urban Economics 51_ , 1–6.

- Conte, M., P. Cotterlaz, and T. Mayer (2021). The cepii gravity database. _CEPII: Paris, France_ . De Chaisemartin, C. and X. d’Haultfoeuille (2020). Two-way fixed effects estimators with heterogeneous treatment effects. _American Economic Review 110_ (9), 2964–96.

- De Chaisemartin, C. and X. D’Haultfoeuille (2022). Difference-in-differences estimators of intertemporal treatment effects. Technical report, National Bureau of Economic Research.

- DESA, U. (2020). International migrant stock: The 2020 revision. _UN DESA: Population Division-International Migration_ .

- Figueiredo, E., L. R. Lima, and G. Orefice (2016). Migration and regional trade agreements: A (new) gravity estimation. _Review of International Economics 24_ (1), 99–125.

- Grogger, J. and G. H. Hanson (2011, May). Income maximization and the selection and sorting of international migrants. _Journal of Development Economics 95_ (1), 42–57.

- Gross, D. M. and N. Schmitt (2003). The role of cultural clustering in attracting new immigrants. _Journal of Regional Science 43_ (2), 295–318.

- Hatton, T. (2005, November). Explaining trends in UK immigration. _Journal of Population Economics 18_ (4), 719–740.

- Mattoo, A., N. Rocha, and M. Ruta (2020). _Handbook of deep trade agreements_ . World Bank Publications.

- Mayda, A. (2010, September). International migration: a panel data analysis of the determinants of bilateral flows. _Journal of Population Economics 23_ (4), 1249–1274.

- McFadden, D. (1973). Conditional logit analysis of qualitative choice behaviour. In P. Zarembka (Ed.), _Frontiers in Econometrics_ , pp. 105–142. New York, NY, USA: Academic Press New York.

18
Figure 2: Gender gaps in Macedonia, Montenegro, Serbia and Turkey <!-- Start of picture text --> 80% 70%<br>Macedonia Montenegro<br>70%<br>60%<br>60%<br>50%<br>50%<br>40%<br>LFP LFP<br>40%<br>Self- 30% Self-<br>30% employed employed<br>Employers 20% Employers<br>20%<br>10%<br>10%<br>0% 0%<br>2007 2011 2007 2011<br><!-- End of picture text --> <!-- Start of picture text --> 80%<br>100%<br>Serbia Turkey<br>70% 90%<br>80%<br>60%<br>70%<br>50%<br>60%<br>LFP LFP<br>40% 50%<br>Self-<br>Self- 40%<br>30% employed<br>employed<br>30% Employers<br>20% Employers<br>20%<br>10% 10%<br>0%<br>0%<br>2007 2013<br>2006 2010<br><!-- End of picture text --> 6
MAKING SENSE OF AFRICA’S INFRASTRUCTURE ENDOWMENT: A BENCHMARKING APPROACH

# **Figure 3.1 Index of infrastructure growth by sector and by region**

<!-- Start of picture text --> Tot. Rd. Density - Indexes Relative to SSA<br>1,600<br>1,400<br>1,200 SSA<br>1,000 EAP<br>800 ECA<br>600 LCR<br>400 MNA<br>200 SAS<br>0<br>1960 1965 1970 1975 1980 1985 1990 1995 2000<br>Mainline Density - Indexes Relative to SSA<br>7,000<br>6,000<br>5,000 SSA<br>4,000 EAP<br>ECA<br>3,000<br>LCR<br>2,000 MNA<br>1,000 SAS<br>0<br>1975 1980 1985 1990 1995 2000<br>Internet Density - Indexes Relative to SSA<br>16,000<br>14,000<br>12,000 SSA<br>10,000 EAP<br>8,000 ECA<br>6,000 LCR<br>4,000 MNA<br>2,000 SAS<br>0<br>Water Access - Indexes Relative to SSA<br>200<br>180 1990<br>160 2002<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>SSA EAP ECA LCR MNA SAS<br>1993 199419951996 19971998 19992000 200120022003 2004<br><!-- End of picture text --> <!-- Start of picture text --> Paved Rd. Density - Indexes Relative to SSA<br>25,000<br>20,000<br>SSA<br>15,000 EAP<br>ECA<br>10,000<br>LCR<br>MNA<br>5,000<br>SAS<br>0<br>1960 1965 1970 1975 1980 1985 1990 1995 2000<br>Mobile Density - Indexes Relative to SSA<br>350,000<br>300,000<br>250,000 SSA<br>200,000 EAP<br>ECA<br>150,000<br>LCR<br>100,000<br>MNA<br>50,000 SAS<br>0<br>Generation Capacity - Indexes Relative to SSA<br>1,600<br>1,400<br>1,200 SSA<br>1,000 EAP<br>800 ECA<br>600 LCR<br>400 MNA<br>SAS<br>200<br>0<br>1980 1985 1990 1995 2000<br>Sanitation Access - Indexes Relative to SSA<br>350<br>1990<br>300<br>2002<br>250<br>200<br>150<br>100<br>50<br>0<br>SSA EAP ECA LCR MNA SSA<br>1990 1992 1994 1996 1998 2000 2002 2004<br><!-- End of picture text --> _Sources_ : As for table 2.1.

22
Pakistan. According to Ravallion and Chen (2006), urban income growth is inequality increasing in the aggregate though this is not the case in rural areas. Two economies where inequality changed little during a long stretch of high growth are Korea and Taiwan (China) because both economies underwent a massive distribution of landed assets just prior to the start of modern economic growth. In other words, the stylized fact here is that, _In the vast majority of cases, economic growth in the developing world has been associated not just with rising incomes but also with rising income inequality (at varying rates). This inequality stems from household income cleavages between the rural and urban sectors, among regions—with coastal regions often registering more favorable economic outcomes—and, to a lesser extent among households in urban areas. Income inequality is severe in cities such as Sao Paolo and Hong Kong and it is high and worsening in cities such as Singapore,_<sup>_19_</sup> _Karachi and Jakarta_ .

Governments view the widening inequality of incomes as an unwelcome development.<sup>20</sup> But as yet, no mix of policies and institutions has arrested or effectively reversed income inequality in rich, middle income, or poor countries. The United States and Japan for a variety of reasons have been unsuccessful in containing creeping income inequality. Similarly, China among the middle income countries, and Pakistan among the lower income ones are both subject to rising income inequality. Although there is no dearth of strategies, policy prescriptions, recipes for institutions, and volumes of macroand micro-level experiences, few economies have been able to achieve the sustained rate of growth they are seeking and even fewer have been able to avert the trend towards a greater concentration of incomes.

# **Income Inequality Does Not Impact on Health Conditions**

Which matters more for urban health, income growth or income inequality? We will argue in the balance of the paper that income growth is critical and with reference to our penultimate stylized fact, income inequality is surprisingly not significant. A careful review of the empirical findings to date by Deaton (2003a) and Wagstaff (2002) suggests

> 19 The Department of Statistics in Singapore reported that the Gini coefficient rose from 0.49 in 2000 to 0.52 in 2005 ("Singapore's Falling Living Standards" 2006).

> 20 On the concerns expressed by the authorities in China, see Yusuf and Nabeshima (2006).

10
TABLE 3: Correlations of MonUtly Average Returns between the GSCI. and Developed and Emerging Stock Markets (Dec. 84 - Jun. 92)

||USA|UK|JAP|GER|SWZ|FRA|HKG|TAI|KOR|MEX|THI|BRZ|IND|GSCI|WLD|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|USA|1.00|||||||||||||||
|UK|.77|1.00||||||||||||||
|JAP|.38|.40|1.00|||||||||||||
|GER|.48|.50|.31|1.00||||||||||||
|SWZ|.60|.59|.40|.69|1.00|||||||||||
|FRA|.59|.54|.46|.66|.63|1.00||||||||||
|HKG|.53|.60|.26|.40|.55|.39|1.00|||||||||
|TAI|.14|.21|.33|.25|.17|.22|.16|1.00||||||||
|KOR|.26|.31|.36|.06|.31|.17|.11|.04|1.00||||||o|
|!.1EX|.40|.38|.28|.32|.42|.31|.30|.35|.16|1.00||||||
|IfrHI|.34|.38|.33|.30|.44|.28|.45|.40|-.01|.37|1.00|||||
|BRZ|.12|.07|.15|.16|.20|.08|.14|.07|.03|-.008|.05|1.00||||
|IND|-.08|-.10|-.27|-.005|-.03|.04|-.04|-. 11|-.05|.02|.08|.03|1.00|||
|GSCI|-.19|-.07|-. 16|-. 10|-.17|-.14|-. 18|-.21|.04|-. 02|-. 22|.03|.11|1.00||
|WLD|.71|.68|.73|.50|.57|.60|.49|.27|.41|.26|.36|.10|--11|-.12|1.00|

Notes: The following abbreviations are used--Japan (JAP). Germany (GER), Swiuerland (SWZ), France (FRA), Hong Kong (HKG). Thailand (THI), Brazil (BRZ), India (IND). Goldman-Sachs Commodity Index (GSCI), World Portfolio (WLD).

Taiwan (TAI). Korea (KOR). Mexico (MEX).

91 observations were used for the Developed Markets and 90 observations for the Emerging Markets and the GSCI.

Data sources: See Tables I and 2.