rafmacalaba/datause-encoder-data huggingface dataset:
# **Table Sup 4: Country level robustness checks**

This table presents robustness checks for Table 1, column 3. Robustness checks are: Column 2: as in (1) but excluding the 10 major oil producing countries for which economic production is expected to be significantly less affected by weather. Column (3): as in (1) but excluding China and USA. Column (4): as in (1) but including a WB region Year FE instead of Year FE. Column (5): as in (4) but without country year trends. Column (6): as in (1) but without Year FE. Column (7): as in (1) but with a linear instead of quadratic country time trend. Columns 8 and 9: as in (1) but including one lag and three lags of growth following an Arellano Bond approach.

||(1)<br>Base|(2)<br>No Oil|(3)<br>No<br>US/China|(4)<br>ContYr<br>FE|(5)<br>ContYr FE<br>+ no<br>Trend|(6)<br>No<br>YrFE|(7)<br>Linear<br>Time|(8)<br>LDV 1<br>Lag|(9)<br>LDV 3<br>Lags|
|---|---|---|---|---|---|---|---|---|---|
|Rainfall|1.185|1.603|1.185|1.456|-0.131|1.607|0.530|1.021|1.007|
||(1.139)|(1.109)|(1.141)|(1.155)|(1.200)|(1.142)|(1.116)|(1.131)|(1.156)|
|Rainfall<sup>�</sup>|-0.310|-0.397|-0.309|-0.434+|-0.179|-0.367|-0.217|-0.256|-0.339|
||(0.253)|(0.247)|(0.254)|(0.253)|(0.241)|(0.253)|(0.247)|(0.252)|(0.266)|
|Temperature|1.727**|1.747**|1.731**|1.907**|1.885**|1.239*|2.240***|1.417*|0.725|
||(0.580)|(0.601)|(0.581)|(0.656)|(0.665)|(0.554)|(0.628)|(0.585)|(0.455)|
|Temperature<sup>�</sup>|-0.061**|-0.062**|-0.061**|-0.068**|-0.074***|-0.051**|-0.079***|-0.060**|-0.037*|
||(0.020)|(0.019)|(0.020)|(0.022)|(0.019)|(0.018)|(0.019)|(0.019)|(0.016)|
|Observations|4,128|3,936|4,080|4,128|4,128|4,128|4,128|3,956|3,612|
|R-squared|0.355|0.380|0.352|0.396|0.233|0.321|0.269|0.383|0.366|

Clustered standard errors at the administrative 1 level in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.1.

18
**Table 5c:  Mexico - Probability of Home-based work (relative to non home-based)***

||**All**|**Men**|**Women**|
|---|---|---|---|
|_Female_|0.044<br>(27.72)|||
|_Age1525_|-0.042<br>(-25.77)|-0.024<br>(-12.49)|-0.071<br>(-19.46)|
|_Age2645_|-0.023<br>(-15.92)|-0.012<br>(-7.4)|-0.040<br>(-12.15)|
|_Head_|-0.007<br>(-4.9)|0.007<br>(3.57)|0.007<br>(1.82)|
|_Married_|0.005<br>(3.97)|-0.008<br>(-5.49)|0.036<br>(10.02)|
|_presch_|0.004<br>(3.00)|-0.002<br>(-1.58)|0.017<br>(4.41)|
|_elemsch_|0.002<br>(1.21)|-0.001<br>(-1.00)|0.006<br>(2.24)|
|_Teen_|-0.000<br>(-0.08)|0.001<br>(1.29)|-0.005<br>(-1.78)|
|_Adult_|-0.003<br>(-2.22)|0.003<br>(2.00)|-0.002<br>(-0.69)|
|_nosch_|0.04<br>(12.28)|0.004<br>(1.35)|0.095<br>(13.28)|
|_pri_|0.014<br>(10.99)|0.003<br>(2.09)|0.033<br>(10.41)|
|Pseudo R<sup>~~2~~</sup>|0.0895|0.0308|0.0966|
|Sample<br>size|94098|60483|33615|

* z-values in parentheses

35
# Table 2. Impact of global shocks on global inflation

|Forecasting horizons|Globa<br>16%|l Demand<br>50%|Shock<br>84%|Glob<br>16%|al Supply<br>50%|Shock<br>84%|Oi<br>16%|l Price Sh<br>50%|ock<br>84%|Inter<br>16%|est Rate<br>50%|Shock<br>84%|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|On impact|0.01|0.03|0.06|-0.06|-0.04|-0.02|0.03|0.05|0.08|-0.06|-0.03|-0.01|
|6 month|0.07|0.15|0.26|-0.22|-0.14|-0.06|0.13|0.22|0.30|-0.20|-0.10|-0.03|
|1 year|0.13|0.26|0.43|-0.35|-0.22|-0.09|0.20|0.35|0.47|-0.31|-0.15|-0.03|
|2 year|0.20|0.38|0.62|-0.50|-0.30|-0.13|0.28|0.49|0.67|-0.43|-0.20|-0.03|
|3 year|0.22|0.44|0.71|-0.57|-0.34|-0.14|0.31|0.55|0.77|-0.49|-0.23|-0.03|

Note: This table reports cumulative impulse response functions (in percentage point) of global inflation factor to positive one-standard deviation global shocks, based on the global FAVAR model that consists of oil price growth, and the global factors of inflation, output growth, and interest rates extracted from the dataset of G7 countries.

31
Policy Research Working Paper 9385

# **Abstract**

This paper investigates the local effects of mining on the quality of public services and on people’s optimism about their future living conditions. It also assesses the mediating role of local institutions and local governments’ taxing rights in shaping the proximity-to-mine effects. The empirical framework connects more than 130,000 respondents from the Afrobarometer survey data (2005‒2015) to their closest mines based on the geolocation coordinates of the enumeration areas (EA) and data on the mines and their respective status from the SNL Metals & Mining. The geo-referenced data are matched with new indicators on local governments’ taxing rights across the African continent. The results suggest that citizens living near an active mine are less likely to approve government performance in key public goods and services—including health, job creation and improving living standards of the poor. On the mediating role of local governance and local taxing rights, the findings point to a negative effect of local corruption, yet a positive effect of local authorities’ discretion over tax and revenues. However, the positive marginal effect of local taxing powers tends to reduce in environments with poor quality of local governance, high incidence of bribe payment and low level of trust in local government officials. Residents of mining communities with low corruption and comparatively high-level of raising revenue ability have the highest rate of positive appraisal compared to the other scenarios.

This paper is a product of the Office of the Chief Economist, Africa Region. 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://www.worldbank.org/prwp. The authors may be contacted at mk4415@columbia.edu or at r.vincent@maastrichtuniversity.nl.

_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
Table 1: Male dominated working sectors

|**Activity/Sector**|**Category M**|**ale percentage Median earning PPP**|
|---|---|---|
|Chemical technician|MDS|100<br>1197|
|Piping/Boil making|MDS|100<br>718|
|Real estate activity|MDS|100<br>299|
|Cobbling|MDS|100<br>279|
|Welding|MDS|100<br>259|
|Metal joining|MDS|100<br>239|
|Fishing|MDS|100<br>199|
|Security guard|MDS|100<br>199|
|Refrigeration and air conditioning [Energy]|MDS|100<br>180|
|General mechanics|MDS|99.83<br>199|
|Transportation of people (bus/taxi) or goods|MDS|99<br>299|
|Auto mechanics|MDS|97.7<br>239|
|Painting|MDS|97.04<br>299|
|Material handling|MDS|96.87<br>479|
|Furniture making|MDS|96.42<br>279|
|Plumbing|MDS|95.77<br>239|
|Priest/Pastor/Imam/Marabout|MDS|92.44<br>199|
|Sports|MDS|92.31<br>199|
|Computer/Electronics/computer and mobile repair [ICT]|MDS|87.78<br>339|
|Electricity [Energy]|MDS|85.72<br>359|
|Artist/art Maker/photographer/musician|MDS|83.49<br>399|
|Teaching and education professions|MDS|82.12<br>399|
|Construction (masonry/scafolding)|MDS|81.47<br>180|
|Mining/oil worker [Energy]|MDS|80.42<br>319|
|Pump operator (gas station)|MDS|76.56<br>319|
|Liberal intellectual and scientifc professions(journalists,<br>lawyers, accountants, etc.)|MDS|75.55<br>479|
|Tutor (private teacher)|Not MDS|74.14<br>798|
|Factory worker/industrial manufacturing|Not MDS|73.71<br>319|
|Sewage and refuse disposal|Not MDS|73.16<br>160|
|Public administration|Not MDS|68.58<br>598|
|Political party leader/executive|Not MDS|67.16<br>120|
|Agriculture/livestock|Not MDS|66.84<br>100|
|Laundry/Textile Cleaning|Not MDS|65.87<br>100|
|Textile: sewing/embroidery/weaving/dyeing|Not MDS|53.12<br>140|
|Health and social work professions (doctors, pharmacists,<br>nurses, other)|Not MDS|48.58<br>287|
|Retail trade: other|Not MDS|41.35<br>160|
|Services in the hotel/restaurant industry|Not MDS|27.22<br>180|

10
# **7 References**

Acemoglu, D. (2003). “Patterns of Skill Premia”. _Review of Economic Studies_ 70, 199-230.

Acemoglu, D. and Autor, D. (2010). “Skills, Tasks and Technologies: Implications for Employment and Earnings”. NBER Working Paper 16082.

- Acosta, P. and Gasparini, L. (2007). “Capital Accumulation, Trade Liberalization, and Rising Wage Inequality: The Case of Argentina”. _Economic Development and Cultural Chang_ e 55 _._

- Atolia, M. (2007). “Trade Liberalization and Rising Wage Inequality in Latin America: Reconciliation with HOS Theory”. _Journal of International Economics_ 71, 467–494.

- Attanasio, O., Goldberg, P. and Pavcnik, N. (2004). “Trade Reforms and Wage Inequality in Colombia”. _Journal of Development Economics_ 74, 331-366.

- Autor, D., Katz, L. and Kearney, M. (2008). “Trends in US Wage Inequality: Revising the Revisionists”. _Review of Economics and Statistics_ 90, 300-323.

- Baffes, J. and Haniotis, T. (2011). “Placing the 2006/08 Commodity Price Boom into Perspective”. World Bank Policy Research Working Paper 5371.

- Barro, R. and Lee, J (2010). “A New Data Set of Educational Attainment in the World, 1950–2010”, NBER Working Paper 15902.

- Boeri, T., Garibaldi, P. and Ribeiro, M. (2011). “The Lighthouse Effect and Beyond.” _Review of Income and Wealth_ 57, S54-S78..

- Bourguignon, F., Ferreira, F. and Lustig, N. (2005). _The Microeconomics of Income Distribution Dynamics in East Asia and Latin America_ , World Bank and Oxford University Press, Washington, DC.

- Brambilla, I., Dix-Carneiro, R., Lederman, D. and Porto, G. (2011). "Skills, Exports, and the Wages of Seven Million Latin American Workers". _World Bank Economic Review_ , forthcoming.

- Card, D. and Lemieux, T. (2001). “Can Falling Supply Explain the Rising Return to College for Young Men?” _Quarterly Journal of Economics_ 116, 705-746.

- Cruces, G., Garcia-Domenech, C. and Gasparini, L. (2011). “Inequality in Education Evidence for Latin America”. Mimeo, CEDLAS-UNLP and UNU-WIDER.

- De la Torre, A., T. Didier, C. Calderon, S. Pienknagura, T. Cordella, C. Aedo, and Walker, I. (2011). “LAC’s Long-Term Growth: Made in China?”, Biannual Report of the Office of the Chief Economist for Latin America of the World Bank.

- DiNardo, J., Fortin, N. and Lemieux, T. (1996). “Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach”. _Econometrica_ 64, 1001-1044.

- Ferreira, F., Leite, P. and Wai-Poi, M. (2007). “Trade Liberalization, Employment Flows, and Wage Inequality in Brazil.” World Bank Policy Research Working Paper Series 4108.

Galiani, S. (2009). “Salarios y Educación en el Mercado Laboral Panameño”. Mimeo.

- Galiani, S. and Porto, G. (2010). “Trends in Tariff Reforms and in the Structure of Wages.” _Review of Economics and Statistics_ 92, 482-494.

- Galiani, S. and Sanguinetti, P. (2003). “The Impact of Trade Liberalization on Wage Inequality: Evidence from Argentina.” _Journal of Development Economics_ 72, 497-513.

- Galiani, S., Heymann, D. and Magud, N. (2011). “Income Distribution, Factor Endowments, and Trade Revisited: The Role of Non-Tradable Goods”. Available online at SSRN.

21
**Table 10: Unorganized Sector Log (Employment) and Log (Real Output): Sub- sample Main States**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||Empl|oyment|Real O|utput|
||_Ot_|_her-sector Emp_|_loyment Spillo_|_vers_|
|Horizontal Employment Spillovers|||||
|from Organized Sector|0.2626***|0.0835***|||
||(0.0347)|(0.0303)|||
|Forward Employment Spillovers from|||||
|Organized Sector|0.1941<br>03345|3.1788***<br>12138|||
||(.)|(.)|||
|Backward Employment Spillovers from|||||
|Organized Sector|1.6498***|1.9515***|||
|Average TFP of Horizontal-linked|(0.2086)<br>_Ot_|(0.4197)<br>_her-sector Prod_|_uctivity Spillo_|_vers_|
|Organized Plants|0.1288**|0.1400**|0.2102++|0.2170++|
||(0.0630)|(0.0572)|(0.1621)|(0.1507)|
|Average TFP of Forward-linked|||||
|Organized Plants|0.6328***|-0.2588|1.3932***|7.7140***|
||(0.1839)|(0.6561)|(0.4883)|(1.2367)|
|Average TFP of Backward-linked|||||
|Organized Plants|0.6549***|0.6369+|0.4836|2.6044***|
||(01760)|(03875)|(04344)|(09898)|
||.<br>_O_|.<br>_wn-sector Empl_|.<br>_oyment Spillo_|.<br>_ers_|
|Forward Employment Spillovers from|||||
|Unorganized Sector|0.3533|0.9201|||
||(0.3740)|(1.2870)|||
|Backward Employment Spillovers from|||||
|Unorganized Sector|1.2230***<br>|2.0634***<br>|||
||(0.1822)|(0.5535)|||
|||_Other-sector O_|_utput Spillove_|_rs_|
|Horizontal Output Spillovers from|||||
|Organized Sector|||0.1968***<br>|0.0545**<br>|
||||(0.0280)|(0.0268)|
|Forward Output Spillovers from|||||
|<br>Organized Sector|||1.6621*<br>|-15.7211***<br>|
||||(0.9108)|(2.8303)|
|Backward Output Spillovers from|||||
|<br>Organized Sector|||2.6949***<br>|14.4461***<br>|
||||(0.5933)|(2.0230)|
|||_Own-sector Ou_|_tput Spillover_|_s_|
|Forward Output Spillovers from|||||
|<br>Unorganized Sector|||0.3873|-1.6927*|
||||(0.3780)|(0.9001)|
|Backward Output Spillovers from|||||
|Unorganized Sector|||0.5417*|-1.3090**|
||||(0.2793)|(0.5999)|
|Constant|-39.4178***|-86.5682***|-121.0611***|68.6633**|
||(6.5028)|(17.9159)|(20.0264)|(32.6279)|
|Observations|4352|4352|4352|4352|
|R-squared|0.1409|0.3858|0.0998|0.3156|

_Note: All specifications contain panel (state-industry) fixed effects as well as year fixed effects. Columns 2 and 4 also includes state-year and industry-year fixed effects. Standard errors are clustered by the state-industry level. Significance at the 20% level is indicated by ++, at the 15% level by +, at the 10% level by *, at the 5% level by ** and at the 1% level by ***._ 39
**Clmeroon:** i **Came** of Adent Boom Management

Cameroon's experience with commodity export booms during the 1970s is interesting for **a** number of reasons. First, it had two positive shockb: a coffee price boom in 1976-77 and an oil boont in 1979-80. (Cameroon did not export **oil** prior to thac time.) Second, while the former was a price shock, the latter involved exploitation of new offshore oil reserves beginning in 1978. Benefits of Cameroon's new oil export capability were greatly enhanced by the sharp run-up in world petroleum prices in 1979-80. Finally, Cameroon"s management of these back-to-back booms was exemplary. Largely through prudent fiscal policy, it avoided many of the adverse consequences of booms experienced by other commodity-exporting countries.

Assessing Cameroon's growth performance is difficult because of data accuracy problems. 19/ The real GDP growth figures reported by the IMF's Inte2national Financial Statistics differ considerably from those in the World Bank's Country Economic Memorandum (CEM), as the Table shows. Nevertheless, the data, such as they are, suggest that real GDP growth drog2e during the 1976-77 coffee boom. As explained above, it is not uncommon to see very little or no surge Ln real GDP in response to a sharp rise in the world price of a country's primary export commodities. Although there may be some reallocation of resources, the overall level of capacity utilization need not be greatly affected, particularly if the economy is near full employment or if unemployment is structural in nature. Hence, although national income rises, real domestic product mnay show little change.

In contrast, the 1979-80 boom initiated by the expansion in oil 19/ These problems are discussed in Cameroon:Countrv Economic Memorsndum. The World Bank, Report No.6395-CM, February 19, 1987.

33
3 that returns are lower for individuals that experienced a recession in the initial years of their career, showing how recessions can have permanent effects via experience losses. We find that economies that transitioned out of communism suffer the obsolescence of past experience, also exhibiting lower returns to experience going forward for many years. We also find that returns to experience are not correlated with initial stocks of experience nor education. This suggests that experience may not suffer from decreasing aggregate returns, and that experience may not be easily substituted by more education.

Third, our accounting framework shows that the contribution of experience to economic development might be as important as the contribution of education. Indeed, education and experience both account for about one third of the income gap between developing and developed economies. Likewise, the long run impact is similar whether developing countries attain the same distribution of education as developed economies _or_ achieve the returns to experience of developed economies. However, raising returns to experience has a _faster_ impact. This is notable as significant reform to the schooling system is likely costly and slow. On the other hand, if reforms that improve the returns to experience are institutional, implementation costs may be lower.

Our study makes several contributions to the literature. We build on a relatively sparse literature on the relationship between experience and economic development (Manuelli and Seshadri, 2014; Lagakos et al., 2018b,a; Dauth et al., 2019; Islam et al., 2019; Deming, 2021).<sup>2</sup> We first produce global estimates of the returns and confirm the results of Lagakos et al. (2018b) who study how wages vary with experience for 125 samples in 18 countries, however for a much larger sample of 1,084 samples in 145 countries.<sup>3</sup> Our sample includes 38 high, 81 middle and 26 low income countries, which allows us to examine whether the returns vary non-linearly with economic development. Second, we account for several empirical challenges in estimating the returns. We use two methods inspired by Heckman and Robb (1985) to attempt to reduce the experience-time-cohort problem when estimating returns to experience.<sup>4</sup> Our large data sets allow us to include decadal cohort fixed effects or country-specific

> 2See Rubinstein and Weiss (2006), Rosen (2008) and Polachek (2008) for surveys of the literature.

> 3Lagakos et al. (2018b) use for robustness checks an expanded set of 263 samples in 35 countries. In a related paper, Islam et al. (2019) use the same 1,084 samples as in the present study to investigate withincountry gaps in the returns to experience between sectors and locations.

> 4Due to collinearity, experience, time and cohort effects cannot be simultaneously estimated. If year fixed effects are added, the estimated experienced effects may then also capture cohort effects.
**The problem with investment fund schemes is** that the tax benefit **may** well be unrelated to the **aaxguIl** investment decision. If **firms** are investing **at** least a quarter of their earnings anyway (this is not an especially high rate of reinvestment), then the scheme in practice is equivalent to one that simply gives firms a one year tax deferral on a quarter of their earnings in exchange for placing these earnings in a government account for a year. While this scheme may benefit the firm, it does not provide any subsidy to new investment. It encourages investment only in the sense that it reduces the effective tax burden on 25% of the fuiture earnings that such investment generates, in precisely the way that a very small reduction in the rate of income tax r would.

# B. heasuring the recuired rate of return

There are several issues relating to the measurement of the required rate of return r. Already discussed above is the need to use realistic rates of return that reflect the risk premia required by the market. In an economy with well-developed financial markets and most investment undertaken by public corporations, the required nominal return to debt i in expression (2) would be well approximated by the observed nominal interest rate, and the required return to equity before personal taxes, /(l-H), could be based on observed returns to equity. One could use either an after corporate tax earnings-price ratio or a market return (dividend yield plus capital gain) for this purpose. A benefit of this approach is that it may not require one to specify the tax treatment of those who supply the funds to corporations.14 In a developing country, such returns to debt and equity may not be as easily observable. In this case, one may need to use information on world interest rates, combined with the tax rules that apply to foreign source 29
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Policy Research Working Paper 6627

# **Abstract**

Household air pollution is the second leading cause of disease in Madagascar, where more than 99 percent of households rely on solid biomass, such as charcoal, wood, and crop waste, as the main cooking fuel. Only a limited number of studies have looked at the emissions and health consequences of cook stoves in Africa. This paper summarizes an initiative to monitor household air pollution in two towns in Madagascar, with a stratified sample of 154 and 184 households. Concentrations of fine particulate matter and carbon monoxide in each kitchen were monitored three times using UCB Particle Monitors and GasBadge Pro Single Gas Monitors. The average concentrations of both pollutants significantly exceeded World Health Organization guidelines for indoor exposure. A fixed-effect panel regression analysis was conducted to investigate the effects of various factors, including fuel (charcoal, wood, and ethanol), stove (traditional and improved ethanol), kitchen size, ventilation, building materials, and ambient environment. Judging by its effect on fine particulate matter and carbon monoxide, ethanol is significantly cleaner than biomass fuels and, for both pollutants, a larger kitchen significantly improves the quality of household air. Compared with traditional charcoal stoves, improved charcoal stoves were found to have no significant impact on air quality, but the improved wood stove with a chimney was effective in reducing concentrations of carbon monoxide in the kitchen, as was ventilation.

This paper is a product of the Sustainable Development Department, Africa Region; and the Environment and Energy 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 pmartin@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