rafmacalaba/data-use-mentions-extended huggingface dataset:
below, there are many explanations for urbanization drivers in India, too many in fact for one study to accurately assess. We seek to quantify whether and how these local conditions, along with other factors like wage costs, promoted or discouraged the urbanization process.

Our study combines data from the Annual Survey of Industries for the organized (formal) sector and from the National Sample Survey for the unorganized (informal) sector. On the whole, India’s manufacturing sector became more urbanized, with the share of workers in urban areas rising from 33% of employees in 1989 to 41% in 2005 (Figure 1a). Urbanization growth was most dramatic from 1989 to 1994, but slowed down from 1994 to 2000. The urbanized employment share was basically flat from 2000 to 2005. This pattern of increasing urbanization was also present when looking just at manufacturing plant counts, but the opposite trend is 1 Key references in this area include Duranton and Puga (2001), Glaeser et al. (1992, 1995), Henderson (2005, 2010), Henderson and Venables (2009), Henderson and Wang (2005, 2007), World Bank (2009, 2011a), Moretti (2004), Rossi-Hansberg and Wright (2007), and McKinsey (2010).

2
treatment only.

Moreover, for the subset of villages where such information is available, we replace the zero/one indicator of program availability ( _MNREGSdt_ ) with the number of days of total or irrigation-related MNREGS works in a village. As the share of the latter varies significantly across villages and effects of irrigation-related infrastructure would be felt more quickly than those of other types of local public goods (drought-proofing or land improvements), differences in estimated coefficients’ significance or magnitude between the two would indicate the relative importance of quick-maturing irrigation-related work: A figure for the latter much larger or more significant than that on total labor would suggest that water-related infrastructure built by MNREGS drives productivity effects while the opposite (i.e. the coefficient on total MNREGS-work being larger or more significant than that on water-related improvements) would point towards programinduced resource transfers as a the main transmission channel.

# **3.2 Descriptive statistics**

Table 2 presents data on key household and individual characteristics in 1999/00 and 2007/08 for treatment and control. Significant declines in household size, from 6.9 to 5.7 members on average, go hand in hand with increases in per capita income or consumption from 10,141 to 23,252 and 5,087 to 8,164 respectively 9
other religions similarly match with those observed in the NSS surveys. Biases observed in the composition of scheduled caste, scheduled tribes (and other classes), share of female headed units and households with extended family members living in the same house are also largely resolved through reweighting.

The one demographic variable for which a bias persists is the share of members aged between 0 and 18 years for which a gap of up to 5 percentage points between the CPHS and the NSS-surveys is observed.

_Asset ownership and access to services:_ Somanchi (2021) also documents that the shares of households with access to electricity, water, toilet and ownership of a television and refrigerator are notably higher in the CPHS -- 2015 and 2019 compared to the 13
between robotization in HICs and less offshoring to LMICs.

**Figure 3: Operational Stock of Robots per 1000 Employees in HICs, by country, 2004-2015**

<!-- Start of picture text --> 4.50<br>South Korea<br>4.00 Germany<br>Sweden<br>3.50 United States<br>Denmark<br>3.00 Belgium<br>Spain<br>2.50 Italy<br>Finland<br>2.00 France<br>Austria<br>1.50 UK<br>Switzerland<br>1.00 Portugal<br>Norway<br>Australia<br>0.50<br>0.00<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br>‐0.50<br><!-- End of picture text --> Note: Calculations based on International Federation of Robotics Database 8
Against this background, this paper aims to enhance the understanding of the linkages between individuals’ time use and socioeconomic status, proxied by asset ownership, in lower-income contexts. We do so by leveraging the unique data from a nationally-representative survey that was implemented in Cambodia in 2019/20 with the goal of conducting private interviews with the adults in each sampled household to gather self-reported information regarding their time use across paid, unpaid and leisure activities, labor market activities, and personal asset ownership, among other topics. The data allow us to address the knowledge gaps in the literature and offer new evidence on the relationships between men’s and women’s time use and their socioeconomic status.

Specifically, we provide a comparative assessment of the relationships between individual-level time use measures and a rich set of proxies for socioeconomic status, including a diverse set of physical and financial assets, across residential and non-residential land, livestock, financial accounts, and durables such as mobile phones and vehicles. The analysis is conducted separately across men and women, and both across and within households. Our regressions allow us to discern not only the association of each proxy for individual socioeconomic status with men’s and women’s time use measures at the national-level, but whether the statistical significance and extent of the association differs across specific sub-populations.

There are five headline findings that reveal a number of stark gender inequalities in time use, as well as relevant channels that appear to be affecting men’s and women’s time allocation. First, the paper demonstrates higher time spent in unpaid work (nearly three hours per day more) by women, including among those who are employed. Women, particularly those working in agriculture, also spend significantly less time in leisure activities.

Second, the specific classes of asset ownership have large and statistically significant associations with time use measures, but that the associations have a stark gender dimension. While asset owners among women tend to shift their time away from leisure towards paid work, asset owners among men shift their
Policy Research Working Paper 7987

# **Abstract**

This paper documents access to services and ownership of infrastructure-related durables in the water, energy, telecom, and transport areas, based on harmonized household survey data covering 1.6 million households in 14 Latin American countries during 1992 to 2012. The paper provides a systematic disaggregation of access and ownership rates at different levels of income and over time, and econometrically derives the country infrastructure premium, a measure of how much a household benefits from simply being located in a given country. The results show extensive inequality of access, within countries across the income distribution, but also across countries for households at similar levels of income. For water and electricity, for example, up to two-thirds of the variability in individual percentile access to infrastructure services and consumption of related assets can be explained by country residence only. In addition, few country fundamentals appear to be significant in explaining this variability, pointing to policy differences as an important determinant. The paper derives the income elasticity of infrastructure access for the full set of indicators, and uses these to estimate the time that would be needed to close the remaining gap for households at different levels of the income distribution under a “business as usual” hypothesis. Under that scenario, universal access appears to be decades away for many countries in the region. The last part discusses the policy challenges, arguing that in a context in which public budgets face strong constraints and significant increases in private investment are unlikely to be forthcoming, a large part of the solution lies in refocused investment strategies, better demand management, and improved public spending efficiency.

This paper is a product of the Sustainable Development 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 mfay@worldbank.org.
**Table 11. Tariff Equivalents of Cross‐border Barriers to Trade in Services**

|||**Tariff**<br>|**equivalent (%)**||
|---|---|---|---|---|
|**Importer**||**σ = 1.95**||**σ = 5.6**|
|Belarus|65.2||119.6||
|Germany|59.4||115.3||
|Slovak Republic|58.3||114.4||
|Czech Republic|56.8||113.2||
|Poland|56.5||112.9||
|Slovenia|56.3||112.9||
|Romania|56.3||112.8||
|Latvia|54.7||111.5||
|Russian Federation|54.3||111.2||
|Greece|54.2||111.1||
|Lithuania|54.1||111.0||
|Bulgaria|53.8||110.8||
|Hungary|53.3||110.4||
|Estonia|51.5||108.8||
|Cyprus|49.4||107.1||

Source: World Development Indicators, World Bank Trade in Services Database, and CEPII. Note: σ is the elasticity of substitution. For robustness, two separate values are assumed: σ � 1.95 and σ � 5.6 ..
methods used in the past. Section II introduces macroeconomic and microeconomic input data used in the analysis. Section III assesses the goodness of fit of three model variations to actual distributions and the effects on poverty, inequality, and growth incidence curves. Section IV presents the final remarks.

# **I. Methodological approach**

The estimates and analysis presented in this paper use an improved micro-simulation model to predict the welfare and distributional impacts of growth. The micro-simulation model superimposes macroeconomic projections on behavioral models built on the last available household survey for each Latin American and Caribbean country. The model is loosely based on previous approaches to microsimulation described in Bourguignon et al. (2008) and Ferreira et al. (2008). The main difference here is the omission of the computable general equilibrium (CGE) component, which is challenging to employ in most developing countries.<sup>4</sup> Instead of a CGE, the approach described in this paper links the behavioral microsimulation model to aggregate macroeconomic data for LAC countries. However, since employment and labor income estimations are usually not available, the output growth estimates must be translated into employment and labor income changes at the sector level. These estimates are typically made using sectoral output-employment and productivity-labor income elasticities based on aggregate output and labor market past data, which are then applied to the output growth projections to generate changes in employment and labor income by sector (Braga, C. et al., 2023).<sup>5</sup> The predicted sectoral employment and income, along with the macroeconomic output projections, are the final inputs for the microsimulation model. This approach has been extended to explicitly consider informality within economic sectors, which comprises a major problem in the LAC region.

This micro-simulation model accounts for multiple transmission mechanisms that affect family labor and non-labor income and captures impacts at the micro level across the income distribution. In particular, the model can consider significant changes in population over time; labor market adjustments in employment and earnings, or
Policy Research Working Paper 6229

# **Abstract**

This paper introduces the Exporter Dynamics Database. The database includes exporter characteristics and measures of exporter growth based on firm-level customs information from 38 developing and seven developed countries, primarily for the period between 2003 and 2010. The measures are available at different levels of aggregation, including: a) country-year, b) country-yearproduct, and c) country-year-destination. Several new stylized facts about exporter behavior across countries emerge from the database. (i) Larger or more developed economies have more exporters, larger and more diversified exporters, and lower entry and exit rates than smaller or developing economies. (ii) In the short run, expansions along the intensive margin (exporter size) contribute more to export growth than expansions along the extensive margin (number of exporters). (iii) Exit rates are highly correlated with entry rates and both are negatively correlated with survival rates, average exporter size, and diversification. (iv) The number of exporters and the entry and exit rates in a country-product group are partially driven by country and productgroup effects; however, the average size of exporters in a country-product group is not. Although the first three facts can be explained by models incorporating firm heterogeneity and uncertainty, the fourth fact is more difficult to explain with existing models. Several findings are confirmed in this database, including the importance of large multi-product firms. This database can be a valuable tool to improve the understanding of the microfoundations of export growth, by providing new insights about exporter characteristics and dynamics.

This paper is a product of the Trade and Integration Team, Development Research 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 tcebeci@worldbank.org, afernandes@worldbank.org, cfreund@worldbank.org and
marry men who are on average 3 years older than them. On average, women participate in 0.3 decisions out of a maximum of 5. Women agree to an average of 0.2 statements out of 5 on when it would be justified for a man to beat his wife. These characteristics are similar across the two samples.

Table A3 presents the summary statistics for the men in each sample. The size of the male sample is 75 to 80 percent of the female sample, since women of childbearing age are over-sampled in the DHS. About 53 percent of the men in the sample are working. The average age of the cohort is 21, a year older than the women’s average age. About a quarter of men have more than secondary education, slightly lower than the women’s share.

# **3 Results**

## **3.1 Main results**

The results of the main marriage penalty estimation are in Table 1. The model collapses the yearly event study indicators into pre- and post-marriage periods, with the full set of birth cohort and country-year fixed effects. The post-marriage treatment indicator is then interacted with a binary variable indicating whether the cohorts exclude women with children (the “no child sample”) or allow for childbirth (the “ignore child sample”).

Panel A shows the results for women across the region (column 1) and then the four constituent countries (columns 2-5). On average, marriage reduces labor force participation by 11.7 percentage points across South Asia among childless women in the five years after marriage. Among our sample countries, the penalty is largest in India, at 12.1 p.p., and lowest in Maldives, at 2.3 p.p., where it is not significant.

Across the region, the marginal effect of allowing for childbearing in the regression specification is small. Whereas the marriage penalty among all women is 15.7 p.p., the marriage
When we use our proxy variables for informal regulatory pressures in Regression 2, we obtain similar results. Formal regulatory pressures are still quite important, and the measured size of the effect is similar to that found in Regression 1. "Other" factors that prove statistically important are size (which also increases abatement activities at a decreasing rate) and competitiveness. In this regression, both SOE and CLEAN are statistically insignificant. The two proxy measures for informal regulatory pressure that prove to be statistically significant are per capita income and location in a large city (LOCl). As discussed above, the measured effect of LOC1 supports our hypothesis that polluters in smaller cities and rural areas are more easily identified and subjected to localized informal pressure. 20

# **4. SUMMARY AND CONCLUSIONS**

In this paper, we have analyzed the results of a survey of pulp and paper plants in four Asian developing countries. We find that both informal and formal regulation have significant effects on abatement. While our results are consistent with a Coasian interpretation, we must defer any strong conclusions until more detailed survey work has been completed.

# **4.1 Determinants of abatement**

The main message of our results is a hopeful one for

> **20** However, it is important to note that many of the plants in **LOC1 have** CLEAN technologies. The fact that CLEAN is statistically insignificant in this regression may be due to its collinearity with LOC1.

25
) is considerably less harmful than corruption that facilitates or encourages poor investments (kickbacks for ignoring very poor quality construction). In terms of the bribe payer, incentives might be aligned by legalizing speed payments (as suggested above) while holding bribe payers responsible for deaths or damage related to improperly licensed construction.

# **Corruption and Infrastructure**

We now turn to infrastructure to see what existing data suggest about the nature of corruption in that sector and possible implications for policy. Aggregate indicators of corruption like the CPI say nothing about the intensity of corruption across sectors. ES at least allow us to assess how petty corruption in infrastructure sectors compares to petty corruption in other areas. It appears that bribery associated with obtaining a utility connection is not much different from bribery in other areas. What does appear more pervasive is bribery associated with construction activities, encompassing infrastructure projects. Construction firms represented in the Business Environment and Enterprise Performance Survey of Eastern Europe and Central Asia have significantly larger „bribe budgets‟ than the average firm, and they bribe more often.

> 3 The exemption of facilitation payments in the United States‟ Foreign Corrupt Practices Act could be justified on similar grounds.

11
# **Labor Supply Responses to Health Shocks: Evidence from High-Frequency Labor Market Data from Urban Ghana**

Rachel Heath, Ghazala Mansuri, Bob Rijkers<sup>*</sup> JEL Codes: J22, O12, I15 Keywords: labor supply, health shocks, Ghana, urban labor market

* Rachel Heath: the University of Washington and BREAD; rmheath@uw.edu; Ghazala Mansuri: the World Bank; <u>gmansuri@worldbank.org; Bob Rijkers: the World Bank; brijkers@worldbank.org. Postal address: Box 353330;</u> Seattle WA 98195. We thank Tyler McCormick and attendees of the 2017 Society of Labor Economists Annual Meeting and the 2017 Northeast University Development Consortium Conference for helpful comments, and Paolo Falco, Mary Hallward-Driemeier, Will Seitz and Dhiraj Sharma for their invaluable help collecting the high frequency labor market data.  The research was supported by funding from the World Bank’s Research Support Budget. The views 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.
from the US International Trade Commission (http://dataweb.usitc.gov/ ). See also Feenstra, Romalis and Schott (2001). Furthermore, historical data on industry level indicators of economic activity at the 4-digit Standard Industrial Classification (SIC) or 6-digit North American Industrial Classification System (NAICS) is also available from surveys posted by the US Census (http://www.census.gov/mcd/index.html ). See also Bartelsman, Becker and Gray (2000).

> 6 Information on US antidumping investigations is published in the US government’s _Federal Register_ publication, which can be accessed on line at <u>http://www.gpoaccess.gov/fr/</u> . The US antidumping cases follow a numerically chronological categorizing process which makes tracking a single case over time through government records very straightforward. While information on European Union antidumping cases can similarly be found in its publicly - available government publication titled the _Official Journal_ (see <u>http://europa.eu.int/eur lex/en/oj/), its case</u> categorizing process is not as transparent so as to allow an individual only minimal effort to be able to track the process of a single case over time.

2
4.<sup>22</sup> Note that the estimated persistence of the value of exports ( _ρp_ = 0 _._ 78) is significantly lower than our baseline estimate for Algeria and Trinidad & Tobago ( _ρp_ = 0 _._ 93). We set _τ_ = 0 since there are no taxes in JS2016. We lowered the intertemporal discount factor ( _β_ = 0 _._ 95) and steady-state transfers ( _Trss_ = 0 _._ 33) to match the long-run interest rate ( _rss_ = 5 _._ 1%) and the optimal level of reserves ( _Ass/Mss_ = _._ 22 _∼_ 2.2 months of imports) in JS2016, respectively (shown in Table 3 Panel B).<sup>23</sup>

> 22JS2016 use annual data from a group of 24 developing countries (sample 1960 to 2014) provided by the World Bank’s World Development Indicators to calibrate the path of detrended non-tradable output, value of exports and the country’s interest rate.

> 23Under the new calibration (aside from discrepancies generated by the linearity assumption) there are two main differences between the models: the elasticity of substitution between non-tradable and imported goods and the structure of the country’s interest rates. In the exogenous income model, we implicitly assume that imported goods and non-tradable goods are perfect substitutes _η_ = _∞_ . Second, the country’s interest rate path is assumed to follow an AR(1) process in JS2016. In our model, the interest rate depends on the country’s net debt, and its persistence
of Peace Research_ 48(2), 249 259.

- [37] Sachs, Jeffrey. 2005. “The End of Poverty: Economic Possibilities for Our Time”. New York: Penguin Press.

- [38] Svensson, Jakob. 2000. “Foreign Aid and Rent-Seeking”. _Journal of International Eco-_ –

- _nomics_ 51, 437 461.

- [39] Temple, Jonathan and Nicolas Van de Sijpe. 2017. “Foreign Aid and Domestic Absorption”. –

- _Journal of International Economics_ 108, 431 443.

- [40] Werker, Erik, Faizal Z. Ahmed, and Charles Cohen. 2009. “How Is Foreign Aid Spent? Evidence From a Natural Experiment”. _American Economic Journal: Macroeconomics_ –

- 1(2), 225 244.

- [41] World Bank. 2017. “The 2017 Global Findex database”.

- [42] Zucman, Gabriel. 2013. “The Missing Wealth of Nations”. _Quarterly Journal of Economics_ –

- 128(3), 1321 1364.

- [43] Zucman, Gabriel. 2017. “The Hidden Wealth of Nations”. University of Chicago Press, Second edition.

22
19|
||[0.058]|[0.079]|[0.087]|[0.086]**|
|Constant|0.00<br>[0.009]|0.01<br>[0.004]***|||
|Observations|817|432|810|418|
|R-squared|0.089|0.078|||
|Number of Countries|40|18|40|18|
|Country Fixed Effect|Yes|Yes|Yes|Yes|
|Adjusted R-squared|||0.036|0.052|
|**First Stage IV Estimates**|||First Stage|First Stage|
|Trade Weighted Growth * Exp|||1.18<br>[.03]***|1.27<br>[.02]***|
|Trade Weighted Growth * Rec|||1.35<br>[.03]***|1.43<br>[.04]***|
|**Underidentification - Weak Identification - Weak**|**Instruments Tes**|**ts**|||
|LM test statistic for underidentification|||92.65|35.91|
|p-value of underidentification LM statistic (Anderso|n or Kleibergen-P|aap)|0|2.07e-09|
|F statistic for weak identification (Cragg-Donald or|Kleibergen-Paap)||1008|856.6|
|Anderson-Rubin chi-sqared test of significance of e|ndogenous regress|ors|15.59|28.69|
|p-value of Anderson-Rubin chi-sqared test of endog|enous regressors||0.000411|5.89e-07|

Source: Authors’ calculations based on World Economic Outlook database 2019.

Robust standard errors in brackets.*** p<0.01, ** p<0.05, *