rafmacalaba/data-use-mentions-extended huggingface dataset:
# **1. Introduction**

Territorial differences in labor earnings are expected to diminish with economic development as barriers to capital mobility decline and technology diffuses within countries. However, they may persist due to poverty traps<sup>1</sup> reflecting delays in subnational institutional development (Galvis and Meisel Roca, 2021) and in economies where mobility frictions are high. By making it costly to trade goods and relocate workers, frictions generate spatial misallocation and slow down aggregate economic growth. Yet, a decline in mobility frictions may not result in measurable improvements in aggregate economic growth when territorial income differences are not exploitable through migration, but rather reflect difference due to the sorting of more productive workers into urban agglomerations. If people lack the endowments that could enable them to earn higher real wages after relocating to high-income areas, migration may contribute to congestion there, and ultimately lower the local productivity premium (Grover, Lall, and Maloney, 2022). Importantly, even in the absence of mobility barriers, territorial income differences may persist and even grow due to market-driven agglomeration forces (Duranton and Puga 2020), which may lead to labor shortages in fast-growing urban centers. Conversely, leveling up may occur as local productivity in leading regions deteriorates and conditions in smaller lagging areas improve. Hence, a priori, it is unclear how large within-country territorial income differences are, how much they have changed over time, and to what extent income differnecs can be exploited through migration.

This paper answers these questions by documenting the territorial differences in labor earnings in fourteen Latin American countries<sup>2</sup> and their evolution between the early 2000s and the late 2010s, using millions of observations from recently released, harmonized micro data from population censuses and household surveys. Exploring this topic in the Latin American context is important for several reasons. First, prior to the mid-2000s, large territorial income differences within the Latin American counties have been documented in the literature, including between Mexico’s North and South (Aroca,
mapping from ICS codes to any product or industry classification system.<sup>17</sup> I deal with this issue by proposing a concordance between 5-digit ICS codes (ICS5) and SIC4 industries. The construction of this mapping involves a three-step procedure. First, I obtain the 10 digit HS codes (HS10) within each SIC4 industry from Pierce and Schott (2009). Second, I search the PERINORM database<sup>18</sup> —the source dataset for the EUESDB— and tabulate the ICS5 codes associate with the set of HS6 codes within each SIC4 industry. Third, I tabulate standards by those ICS5 codes in the PERINORM dataset and select the ICS5 codes whose standards are actually related to the industry into which they were classified in step two. “Terminology” or “vocabulary” standards are not taken into account. Table 3 presents this concordance and the description of the ICS codes within each industry.

The theoretical model suggests that the heterogeneity of product standards across market destinations is a barrier to trade. I define the non-harmonized share of standards for industry _i_ in year _t_ ( _NHt_<sup>_i_)—aproxyforthisNTBmeasure—asthenumberofCENELECstandardsthat</sup> are not “identical” to an existing IEC standard as a share of the total number of standards in each SIC4 industry. I also compute the tariff rate for industry _i_ in year _t_ ( _τt_<sup>_i_)astheweighted</sup> average rate across all 6-digit HS products within each SIC4 industry, using EU’s import value from the U.S. as weights. For some products, tariffs were binding to zero by year 2000 due to the Information Technology Agreement (ITA), which is a tariff cutting mechanism enforced by the WTO between nations accounting for at least 90 percent of world IT trade. These zero-tariff bindings were on an MFN basis and thus available to exports from any other WTO member country.

Table 4 reports average tariff and non-tariff trade costs across SIC4 industries for five-year interval from 1992 to
wisdom suggests that lower oil prices should affect the Gulf States more severely than the overall emerging markets. The finding that Gulf States’ index is less affected than the overall emerging market index suggests that other channels, above and beyond the lower oil revenue channel, might be at play.

Table 5.3 MSCI Gulf States Index

|VARIABLES|∆log (Index)|∆log (Index)|
|---|---|---|
|∆_Log( Oil Price)_|0.0714<br>(0.0773)|0.0554<br>(0.0617)|
|Lags|No|Yes|
|Constant|-0.000235<br>(0.000444)|-8.04e-05<br>(0.000401)|
|Observations|699|696|
|R-square|0.018|0.121|
|Robust sta<br>*** p<|ndard errors in paren<br>0.01, ** p<0.05, * p<|theses<br>0.1|

To investigate the possibility further, we examine the impacts of lower oil prices on individual important oil-exporting emerging markets. Key emerging oil exporters - Brazil, Colombia, Mexico and the Russian Federation - show tremendous sensitivity to the declines in oil prices. The coefficients are much larger than the overall MSCI Emerging Market Index, and the Dow Jones U.S. Market Index. In particular, a 10% decline in the WTI oil price reduces the stock index of Brazil by 3.01%, Colombia by 4.13%, Mexico by 2.21% and Russia by 4.57%. The declines here suggest heavy capital flight of investors from these markets when they see oil prices drop. Since these countries are large and likely systemically important, the magnitude of the impacts is concerning. The indices of many smaller Gulf States, however, are not
magnitude of a standard deviation according to the different indexes. For example, in the case of the IHD, a standard deviation is equivalent to a hurricane with a sustained wind speed of 74 mph (SS Scale 1) hitting an area with 2.3 percent of the population, or one with a sustained wind speed of 111 mph (SS Scale 3) in an area with 0.5 percent of the population. For WEI, a standard deviation is comparable to a hurricane affecting 10.6 percent of the country with a sustained wind speed of 74 mph, or one affecting 7.1 percent of the country’s territory with a sustained wind speed of 111 mph. To illustrate this, consider Hurricane Mitch which hit Honduras in 1998 with a MSWS of 130.6 mph.<sup>21</sup> Given these parameters, due to the hurricane, the model predicts a decrease in per capita GDP growth of 1.1, 3.1, and 1.9 percentage points for MSWS, IHD, and WEI, respectively.

> 19 For example, the IHD index (population‐weighted wind speed) powers wind speed to the 3.8, hence unstandardized coefficients are simply smaller than the MSWS and WEI indexes.

> 20 Column (1), without controlling for serial and spatial correlation, only shows significant results for IHD but not for the other two indices (MSWS and WEI). When correcting, Column (2) results consistent negative and significant estimates.

> 21 Its WEI was 30.41 and its IDH was 699,548.

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money than maleowned firms (10 percent vs. 18 percent). Both differences are statistically significant at the 1 percent level. The indication may be that women firm-owners are more experienced with mobile money than male-owned firms and thus ease of use is not a barrier to adoption. It also may be that female-owned firms engage in smaller transactions and thus do not see high fees as a barrier to adopting mobile money as male-owned firms. It is also worth noting that 20 percent of femaleowned firms and 25 percent of male-owned firms that did not adopt mobile money cite “don’t know enough” as the reason why. This may imply there is scope for awareness campaigns to improve mobile money adoption.

> 6 The survey question on proportion of sales sold on credit has been removed from recent rounds of the Enterprise Surveys and thus the Kenya 2019 survey does not have this information.

> 7 Note that this excludes Zimbabwe.

> 8 Note that Kenya is excluded as the exact survey question was not included in the questionnaire.

11
Figure 1: Long-term versus spot contracts and uncertainty <!-- Start of picture text --> Surplus<br>VC<br>VP<br>VA<br>VU<br>C P A U<br>r ∗ rC rP rU Mean preserving spread<br><!-- End of picture text --> _Notes:_ C, P, A, and U denote regions where dominant arrangement is, respectively, long term contract, spot contract, autarky, and unconstrained cultivation. Dashed portion of _VU_ curve is unattainable given absence of competitive spot markets.

# **3 Context**

## **3.1 Groundwater markets survey**

Our data come from a randomly selected survey of about 2300 borewell owners undertaken in 2012-13 in six districts of Andhra Pradesh (AP) and Telangana (until 2014, also part of AP). The districts were selected to cover a broad range of groundwater availability, conditions for which generally improve as one moves from the relatively arid interior of the state toward the lusher coast.<sup>22</sup> Drought-prone Anantapur and Mahbubnagar districts were originally selected as part of a weather-index insurance experiment (Cole et al., 2013); all 710 borewell owners were followed up from that study’s 2010 household survey. Guntur and Kadapa districts, which fall in the intermediate range of rainfall scarcity, and the water-abundant coastal districts of East and West Godavari, each contribute around 400 borewell owners. All in all, our survey obtained information on 2,411 borewells in 144 villages (21-25 per district). At the time of the survey, none of the plots on which these borewells were situated

> 22Our sample is broadly representative of areas where groundwater is sufficient for _rabi_ cultivation and where it is the sole source of irrigation for that season (canal command areas were avoided).

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by family planning rather than health facilities: unwanted births or pregnancies, and recent birth or pregnancy. Even if lower child mortality leads to lower desired fertility, it is, for example, harder to avoid unwanted births or pregnancies unless one has regular access to family planning services.

Table 6 shows the effects of family planning on the last birth or current pregnancy being unwanted. The results should, however, be interpreted with caution because around 80 percent of women have had access 25The corresponding results using any health facility access are available on request, but lead to qualitatively similar results.

> 26It should be kept in mind that this includes mortality after age 5 and the sample consists solely of women with no schooling. For comparison the 2005 Ethiopian DHS show an under 5 mortality rate of 123 per 1000 live births for the 5 years preceeding the survey, 141 per 1000 live births for the period 5 to 9 years before the survey, and 165 per 1000 live births for the period 10 to 14 years before the survey. In addition, the under 5 mortality rate for women with schooling for the 10 years before the survey was 139 per 1000 live births (Central Statistical Authority of Ethiopia and ORC Macro 2006).

> 27The reduction in mortality among younger women is consistent with the delay in fertility among very young women. This delay would lead to higher birth weight and therefore higher survival probability for each birth.

19
This study used Babajob data to identify the skills demanded by employers in two ways. The first method was to review employer qualification screening questions, and the second was to apply text analysis to capture the demand for skills as expressed in the text of job descriptions. Figure 4 presents the most commonly asked screening questions by occupation level.<sup>9</sup> Four broad categories of screening questions were identified: (i) skills; (ii) personal characteristics; (iii) work conditions and benefits; and (iv) other. The skills category includes overall education level and academic credentials, as well as computer skills, language skills and relevant occupational experience. The work conditions and benefits category includes location or distance to work, salary, and the proposed terms of employment. The “other” category includes uncommon and job-specific questions.

The data reveal that skills-related questions are the most common category of screening filter, though the skills requested differ by occupation level. Skills-related questions appear in about 50 percent of qualifications screenings for most occupation levels, including managerial (50.7 percent) and professional positions (47.9 percent). However, while employers searching for professionals and associate professionals tended to ask about education levels and specific technical skills, occupational experience appears to be more relevant for clerical staff, service and sales workers, and construction and craft workers. Language skills, most often English and Hindi, came up more frequently for managerial and sales positions.

The relatively high frequency of personal information questions demonstrates the importance employers place on collecting basic information, especially for service-related hires in the informal sector, such as maids, cooks and gardeners. Personal information inquiries include questions on the applicant’s gender, age, police verification certificates, as well as requests for resumes and photos. The applicant’s acceptance of the stated employment terms, including the proposed salary and work hours, is another important filter for recruitment decisions.

> 9 Occupational levels are defined according to the ISCO classification. Employers can
obtained. Using the available data, initial investment and operation and maintenance costs per unit of KtCO2e abatement are calculated. Average per unit capital costs and operation and maintenance cost of abatement across the CDM projects categorized by project types are calculated and then used as proxies for the projects for which such data were not available.

The present value of emissions abatement costs for each project are calculated as described in equation (6). The operation and maintenance costs are discounted using real interest rates for the year of fixed capital investment (i.e., the prior year of credit start period). Real interest rates in the host countries are used for unilateral projects, while the rates in the partner countries are used for bi- and multi-lateral projects. Real interest rates for the host and partner countries are obtained from the World Bank (WDI 2010). For the electricity generating CDM projects, the net present value of emissions abatement costs are calculated by subtracting the sum of the discounted flow of electricity sales revenue from the present value of total costs. Wholesale electricity tariffs in different host countries obtained from the PDDs are used to calculate the flow of revenues from electricity sales. Real interest rates are used to discount those revenues. As implied by duality, the abatement cost function includes the sum of the discounted-weighted flows of CERs and electricity outputs. Real interest rates as mentioned above are used to discount those streams of outputs. Table 3 presents the categorical means and standard deviations of the (discounted) total amount of emissions abatement and electricity outputs over the life of the projects and net present value of total abatement costs of the projects, for which all information are available. Wholesale electricity tariffs in some of the host countries were not available, leaving 6,326 observations for use in the empirical analyses.

# **4 Estimation Results and Discussions**

The log-transformed net present values of the total cost of mitigation by each individual CDM project are plotted against corresponding total abatement and presented in figure 2.<sup>11<
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and immune to the influence of local governments, and the central government should complement GDP statistics with objective measures such as those based on night lights and other sources of nonmanipulatable data. Third, while there are likely positive effects from tournament competition among regional governments in China, as the literature has demonstrated, and the target-setting practices consistent with the ratchet principle tend to limit the extent of GDP manipulation, as we show here, our results suggest that we should also consider the negative side of tournament competition among local governments. Moreover, as we document that peer competition could make performance manipulation increase over time due to peers-reinforcement, even if the tournament competition design begins as a beneficial system for motivating bureaucrats, the dynamics of tournament competition could make adverse effects of performance manipulation rise over time. Thus, if we are to preserve the benefits of tournament competition, it is crucial to make performance non-manipulatable. All these implications are recognized by top business leaders. Legendary former Intel CEO, Andrew Groves, emphasizes the notion of paired statistics for management, such as pairing the number of deals closed with the retention rate of clients.<sup>49</sup> It appears that bureaucrat management could benefit from similar management disciplines, such as by pairing GDP growth with indicators of adverse effects of singleminded growth such as pollution and inequality.

# **References**

- Adams, F. Gerard, and Yimin Chen. 1996. “Skepticism about Chinese GDP Growth – the Chinese GDP Elasticity of Energy Consumption.” _Journal of Economic and Social Measurement_ 22 (4): 231–240.

- Aghion, Philippe, and Jean Tirole. 1997. “Formal and Real Authority in Organizations.” _Journal of Political Economy_ 105 (1): 1-29.

- Asher, Sam, and Paul Novosad. 2020. Rural Roads and Local Economic Development. _American Economic Review_ 110 (3): 797-823.

- Ashraf, Nava, and Oriana Bandiera. 2018. “Social Incentives in Organizations.” _Annual Review of Economics_ 10:
Note: The left panel plots average effectively applied import tariff imposed by China during 1992-2005. The right panel plots average effectively applied export tariff faced by China during 1990-2005. Data based on WITS-TRAINS database.

Table 5 reports the findings when tariff shocks are controlled for. Panel A shows the effect of FDI inflows on structural transformation, and Panel B the effect on school enrollment. Increased FDI presence has an even larger impact on structural transformation: a one percentage point increase in FDI shock now reduces change in agricultural employment share by 3.1 percentage points, and raises the change in industry and services employment share by 1.8 and 1 percentage points respectively. Import and export tariff shocks do not seem to have significant impact on the pace of structural transformation. They do affect school enrollment strongly, lower export tariff and higher import tariff lead to higher growth in college enrollment. FDI inflow shock still promotes high school and college enrollment. These results suggest that the effect of FDI entry on local structural transformation and school enrollment is not driven by China’s concomitant trade liberalization.

Table <u>5. Robustness check: control tariff shocks</u>

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
||Panel A:<br>|structural transf<br>|ormation<br>|Panel B: schoo<br>|l enrollment<br>|
|Dependent var|∆agri_emps|∆indu_emps|∆serv_emps|∆Highschool|∆College|
|FDI_shock|-3.105***|1.825***|1.036**|0.754**|0.523*|
||(0.930)|(0.678)|(0.416)|(0.304)|(0.
|Yes|
|Municipality FE|Yes|Yes|Yes|Yes|Yes|
|f(Distance to homeland<br>border,in km)|Linear Inter|Cubic Inter|Cubic<br>BSpline|X,Y,XY|Cubic<br>X,Y,XY|

Notes: Data from the 1996 and 2011 population census at the community (sub-place) level. Each column corresponds to a separate OLS regression using a sample of communities within 30 kilometers of the former homeland borders (on both sides). The dependent variable is the difference in log per capita income for 2011-1996. Columns 1 to 3 include different functions of the linear distance between communities and the homeland borders. Columns 4 and 5 instead include different functions of the geographic coordinates (lat./lon. – X/Y). All regressions include 1996 controls and municipality fixed effects. 1996 controls include: linear distance to former homeland border, share of white, colored and Indian/Asian population, share by age group (0-9, 10-19, 20-39, 40-59, 60+), household head education, share employed, share male, per capita income, total population, share connected to electricity grid, share no refuse, share with piped water. All control variables are interacted with the homeland indicator. Regressions are weighted by community population in 1996. Heteroscedasticity robust standard errors in brackets clustered at the municipality-homeland level. ***p<0.01, **p<0.05, *p<0.1
Ninis, which doubled from nearly 0.66 to 1.28 million between 2000 and 2010, combined with the stabilization of the number of female Ninis at around 3.50 million during the 2000s. In relative terms, the proportion of Ninis in Mexico has been stable since the beginning of the 2000s, at around 22.7 per cent, due to the sizeable increase in the percentage of male Ninis, which went from 7.5 to 12.0 percent between 2000 and 2010, and the slight decrease in the percentage of female Ninis, which went from 36.3 to 33.7 percent during the same period.

The literature has produced several empirical insights into the phenomenon of Nininess in Mexico. Arceo-Gómez and Campos-Vázquez (2011) apply cross-sectional analysis to a combination of census data, household expenditure surveys, and labor surveys covering the period from 1990 to 2010 to study Ninis aged between 15 and 19 years old. In line with the results of De Hoyos et al. (2014), they find that the percentage of Ninis decreased during these two decades. They also find big differences by gender, as well as differential impacts of recessions - which disproportionately affect the young - on the proportion of Ninis. ArceoGómez and Campos-Vázquez (2011) estimate that in 2010 there were 8.6 million Ninis aged 15 to 19 in Mexico (approximately 29 percent of this age group), of which 6.5 million were women. Analyzing the reported reasons for not working, they find 70 percent of women with children do not have anyone who can look after them. This finding, combined with high pregnancy rates in Mexico (Azevedo et al., 2012), supports the hypothesis that teenage pregnancy limits the labor force participation of women and, by motivating their decision to instead spend time on housework, increases the proportion of Ninis in the population. Finally, the authors conclude that household income is an important correlate of being a Nini for men but not for women. Using different sources of cross-sectional