rafmacalaba/data-use-mentions-extended huggingface dataset:
channel. As mentioned in Section 2.1, controlling for everything else, a reduction in import tariffs should increase domestic competition and hence boost labor productivity. The present study uses tariff variations to identify the link between NAFTA and labor productivity via the import-competing channel. Nevertheless, we complement this approach with a pseudo-experimental procedure that identifies all other tradeproductivity channels discussed in Section 2.

As discussed in Section 2, theoretical models with heterogeneous firms suggest that trade reforms will impact asymmetrically on different types of firms. We expect integrated firms to be positively affected by the reforms relative to non-integrated firms. Moreover, the impact within integrated firms could be different depending on a firm’s integrated status. This idea is not only based on theoretical considerations but also appears to emerge from the descriptive statistics presented in Section 3 suggesting that plants within different “integration status” show a different productivity evolution over time. Hence, a crucial identifying assumption behind the pseudo-experimental approach adopted in this paper is that the reforms introduced by NAFTA had a different effect on pre-reform integrated and non-integrated firms.

Our strategy builds on the previous work by Pavcnik (2002) and L ́opez-C ́ordova (2003) analyzing the impact of trade reforms in Chile and Mexico, respectively. While L ́opezC ́ordova (2003) exploits tariff variations Pavcnik (2002) uses a quasi-experimental approach (i.e. treatment versus control group). The mayor difference between these two closely related studies and the empirical approach followed in this paper are the following:

1. Pavcnik (2002) defined a firm as being integrated when it belonged to a “integrated” sector—at 4 digits of the ISIC classification—regardless of the firm’s integration status. Thanks to data availability, in this paper we define the integration status at the firm level.<sup>11</sup>

2. Within integrated firms, our approach allows for a heterogeneous impact of the reforms among firms with different integration status, i.e. exporters, importers or fully
0,017|0,0001|
|North region|-0,826|0,070|0,0001|-0,732|0,040|0,0001|-0,679|0,036|0,0001|-1,092|0,038|0,0001|
|Northeast region|-1,293|0,030|0,0001|-1,247|0,018|0,0001|-1,339|0,018|0,0001|-1,372|0,021|0,0001|
|West-center region|-0,822|0,055|0,0001|-0,552|0,030|0,0001|-0,417|0,029|0,0001|-0,569|0,034|0,0001|
|South region|0,061|0,033|0,0684|-0,107|0,021|0,0001|-0,166|0,021|0,0001|-0,152|0,025|0,0001|
|R2|0,119|||0,085|||0,099|||0,115|||

Source: Based on "Pesquisa Nacional por Amostra de DomiCilios" (PNAD) of the 1976 and 1996.

Note: * People older than 10 years

**Table A3.4: Dependent variable: Total members of households younger than 14 years**

|||||||Ye|ar||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||1976|||1981
more vulnerable to bribery. In column (3), we interact bribery with a dummy for firms greater than 10 years old. In this interaction, firms who are older have an average 21 percent higher sales growth than young firms. In column (4), bribery is interacted with sales and age. In this specification, the coefficient on the age and bribery interaction term is positive but not significant.

Selection bias due to sample composition is a concern since bribery statistics is restricted to firms that conducted at least one business transaction. However, the direction of the bias that could emerge from the selection is not clear. Including only firms doing business transactions does not necessarily negatively bias the role of bribery since these firms may be better suited to deal with bribe seekers. Table 8 shows results including firms that did not conduct any business transactions. We assume these firms did not experience bribery. The sample increases by over 2,000 firms and there are 13 additional bribery clusters. IV estimates are shown with as

> 7 Estimated using Eq (4).

> 8 This effect is calculated using Equation (4). The total effect is calculated at the 25th and 75th percentiles of sales and then a difference is taken.

18
TFP or the total factor productivity is constructed following the methodology of Ackerberg, Caves and Fazer (2015) building on Levinsohn and Petrin (2003) using intermediate inputs as proxy.<sup>5</sup> Since Prowess does not have reliable employment information, the total wage bill is used to measure labor inputs. Gross fixed assets are constructed by the perpetual inventory method Value added, defined as gross output minus the value of material inputs, energy and service inputs, is used as dependent variable in the production function. All relevant values are deflated using sector specific Indian wholesale price indices provided by the Office of the Economic Adviser of the Indian Ministry of Commerce and Industry. The service sector deflator is constructed from the National Accounts Statistics series on the service sector contribution towards the gross domestic output.

To measure service inputs, all expenditures incurred for royalties, technical know-how, license fees, research and development, rent & lease rent, selling & distribution, finance and insurance, outsourced manufacturing and outsourced professional jobs, travel and communication expenses, and repair and maintenance are considered. The variable service intensity measures the intensity of services used in the production and is measured by the share of expenditures spend on service inputs relative to total expenditures.<sup>6</sup> We further disaggregate services and look separately at complex services and IT related services. Complex services are considered as having a greater level of production complexity because of its higher fixed training costs (Costinot, 2009). Complex services are broadly defined as high value-added and high-skill intense services, which usually require strong domestic institutions and the rule of law, because contracting for them is often more complicated than contracting for traditional services. Such services include finance, insurance, securities and pension management, technical, trade and other business services.<sup>7</sup> We also examine the role of service imports in an extension to the baseline.

We control for firm size and the (log) expenditures on services in the vector Xist ,
- 32 -

# What Information is Needed?

Educational and economic outcomes. costs. and the implementation performance of schools In current U.S. practice, educational achievement data hold pride of place: equity concerns lead to collection and reporting of the data not only by school and district, but also by socio-economic characteristics of students. These data are supported by a range of management information on enrollments, staffing, costs, facilities, and so on. Implementation processes are assessed through surveys, observation, qualitative analysis, tacit knowledge, and, less frequently, special studies. Accreditation studies provide a basis of formative information on overall institutional quality.

Information on the economic outcomes of general education is not routinely assembled at the institutional level; perhaps because of the failure of the VEDS system, there is also very little information on the employment outcomes of vocational training.

The absence of data on educational and economic achievement is the most glaring weakness in most developing country contexts, not only for project institutions, but for the system as a whole. The Kenya example cited earlier provides one of the few exceptions. Data on the unit costs of education of various kinds is equally weak. Management information systems have a spotty history, and information on implementation at the school level is exceedingly rare.

The consequences for governments and the World Bank have been discussed at length. A great deal of information is available on inputs and aggregated project costs; very little is available on the factors that permit learning about the effectiveness of schools, projects or systems.

Much of this is attributable, of course, to the general failure to address crucial data needs in the design of M&E investments, and to the failure of most investments in M&E capacity. In particular, the failure to establish achievement testing systems in many countries has made it impossible to assess the educational effectiveness of investments. The attempt to establish tracer studies of employment outcomes has similarly failed in most countries. Declining levels of Bank supervision, larger and more complex projects and
The survey was issued to 70 entities that are active investors in the power sector of SSA. 51 surveys were completed by individuals at 48 of these entities, resulting in a response rate of 69%. It contains four sections: 1) Investor details: Participants provided contact details, their area of work within the power sector, and their favored segment of the supply chain. 2) Investor experience: Participants listed countries in which they have invested in the power sector, the segment of the supply chain they invested in, and their overall investment experience (positive, mixed, negative) in each case, 3) Investor perceptions: Participants rated the readiness of the regulatory arrangements of each segment of the supply chain in SSA and of countries in SSA (positive, mixed, negative). 4) Importance of risks to investors: For each risk category, participants ranked constraints according to how important they are when making an investment. They also ranked the three risk categories.

Aggregate data were collected from various public sources, including Aisenman et al’s (2010), Kojima and Trimble’s (2016) and the World Bank’s _RISE_ and _WDI_ indicators. Data were also collected from internal World Bank documents. Using the survey data, we produce the following statistics on investors’ priorities when making an investment decision: First: Overall risk category score (between 0-10) to answer the question whether – on the highest level of risk aggregation – policy and regulatory risk, power sector context risk, or country context risk is the most important risk category. Second: Risk factor scores – disaggregating the three risk categories into the 10 underlying risk factors – to further understand what drives the importance of risk category scores (e.g., whether the importance of the policy and regulatory environment to investors is driven by concerns around the ease of market entry, clarity of investment priorities or the certainty of cash flow). Third, risk constraints – on the lowest level of aggregation – which describe for each
0.004|-0.087|0.071***|-0.053|
||||||(0.098)|(0.096)|(0.017)|(0.085)|
|Enjoy handling new problems|||||0.122|-0.033|0.008|-0.017|
||||||(0.143)|(0.140)|(0.033)|(0.131)|
|Enjoy trying to solve complex problems|||||0.129|0.119*|0.065***|0.157**|
||||||(0.082)|(0.065)|(0.023)|(0.070)|
|Curiosity is a driving force for her actions|||||0.034|0.106|0.001|0.084|
||||||(0.081)|(0.077)|(0.011)|(0.076)|
|Observations|6,245|6,333|6,553|6,320|6,245|6,333|6,553|6,320|
|R-squared|0.485|0.458|0.233|0.478|0.496|0.473|0.238|0.487|

_Source_ : Data for the study comes from a survey of farmers in northern Uganda. The survey was conducted by Innovations for Poverty Action.

_Notes_ : This table presents OLS regression results for equation (1). For each column, the outcome variable is (an increasing) categorical variable (1-4) which measures the openness to vote for a political party, namely, the Democratic Party (DP), the Forum for Democratic
We estimate equation (1) using the _system-GMM estimator_ of Arellano and Bover (1995) and Blundell and Bond (1998), which addresses the potential biases that arise from the correlation between the firm fixed effects and the lagged dependent variable, as well as the endogeneity of sales, and cash flow in short panels. We treat all of the firm specific variables as endogenous, and use lagged values dated _t_ -2 and _t_ -3 as GMM-type instruments.<sup>5</sup> Reported standard errors are robust and they are clustered at the five-digit industry level.

# _3. DATA_

The firm level variables are from Prowess, a panel data set of Indian firms, collected by the Centre for Monitoring of the Indian Economy. The data account for about 70% of the organized industrial activity. Firms are classified into industries based on the 2008 National Industrial Classification (NIC).<sup>6</sup> We use data on manufacturing firms for the 1989-2000 period. We drop the observations in the top and bottom 1% of the sample based on investment rate, sales and cash-flow in order to eliminate outliers. To construct firmlevel investment expenditures, we take the annual difference in the gross fixed assets, which measures the value of the firm's capital.

The data on licenses, which represent the fraction of products in an industry subject to licensing requirements, are from Topalova and Khandelwal (2010). The data vary across four- or five-digit industries and over time. Delicensing in India during the 1990s was accompanied by other industrial reforms that included trade liberalization (reductions in tariffs), and lowering of entry barriers to foreign investment. In order to identify the distinct effects of delicensing, we also control for these concurrent reforms. The data on tariffs and the share of products which have approval for foreign investment (FDI) are also from Topalova and Khandelwal (2010). Additionally, we control for the logarithm of real net state product (source: Reserve Bank of India)
2

# I. **INTRODUCTION**

Developing countries—understandably—often show more interest in learning from the health systems of industrialized economies, rather than from one another’s. For the developing countries of East Asia, one especially relevant group of industrialized economies are Japan and the Asian Tigers (Hong Kong (China), the Republic of Korea, Singapore and Taiwan (China)). It is true that even countries such as China, Malaysia and Thailand (the richer developing countries in East Asia) lag far behind Japan and the Tigers in terms of per capita income, and that on present trends they may well never catch up ( **_Figure 1_** ).<sup>*</sup> But in terms of health system challenges and solutions, the gaps are smaller than per capita income gaps suggest—both within the Japan-Tiger grouping, and between the Japan-Tiger grouping and the developing countries of East Asia.

_Figure 1: Per capita incomes in selected East Asian economies, 1960-2003_<sup>_†_</sup> <!-- Start of picture text --> 40,000<br>China<br>Hong Kong, China<br>35,000 Japan<br>Korea<br>Malaysia<br>30,000<br>Singapore<br>Taiwan, China<br>25,000 Thailand<br>20,000<br>15,000<br>10,000<br>5,000<br>0<br>1960 1965 1970 1975 1980 1985 1990 1995 2000 2005<br>GDP per capita $US 2000 prices<br><!-- End of picture text --> All health systems face the problem of how to pay providers. Japan, richer than the Tigers, has been most successful in devising a non-inflationary and non-distortionary fee schedule, but it is Korea and Taiwan (China) that are ahead in introducing prospective payment methods. Policymakers in
# **I. Introduction**

Youth unemployment and underemployment across much of the developing world is extremely high. Two facts highlight the importance of youth’s labor in the world economy: 17 percent of the world’s population are youth (ages 16-24) and youth make up 40 percent of the world’s unemployed. In developing countries, where labor frequently encompasses informal self-employment and small-scale agriculture, youth also struggle with high underemployment (they are not able to work as much as they would like to) and low productivity. Up to two-thirds (60%) of the young population is underutilized in some developing economies, meaning that they are unemployed, in irregular employment – most likely in the informal sector, or neither in the labor force nor in education or training (ILO, 2013). Youth unemployment and underemployment not only slow down economic growth but also negatively impact crime rates (Fella and Gallipoli, 2007), depression rates (Frese and Mohr, 1987), substance abuse rates (Linn, Sandifer and Stein, 1985), and rates of social exclusion (Goldsmith, Veum and Darity, 1997).

Nepal is similarly affected by youth unemployment and underemployment. With a per capita income of US$700, Nepal is South Asia’s second poorest country (ahead of only Afghanistan). Helped by remittances, the proportion of the population falling below the national poverty line has declined in recent years from 31 percent in 2003-04 to 25 percent in 2011 (Central Bureau of Statistics 2011). One underlying factor of poverty in Nepal is the lack of employment opportunities, and a reliance on self-employment in the agriculture sector, which accounts for 61 percent of the total labor force (Nepal Living Standard Survey 2011). The unemployment rate for those aged 15-29 is 19.2 percent, compared to just 2.7 percent for people older than 15 (ILO 2014). Faced with these prospects, young Nepalese are compelled to consider migrating overseas in search of better opportunities.

Governments worldwide
OZIER - REPLICATION REDUX – p. 31 of 41 (particularly since most of these efforts are successful given code availability, as in Figure 3), but the discovery of a problem in re‐running an analysis _is_ new information. The problem is not limited to editors’ survey responses: Gertler, as chair of 3ie’s board of directors, saw many of the 3ie replications unfold firsthand. He and his coauthors report that of 27 replication studies 3ie commissioned, 20 upheld the original results, while 7 reported being “unable to fully replicate the results in the original article.” Galiani, Gertler, and Romero note: “The only replication published in a peer‐reviewed journal claimed to refute the results of the original paper,” citing the present case of Davey, et al. (2015).

Before making any recommendation, however, Galiani, Gertler, and Romero have led by example, following in a long tradition. Replication efforts that focus on a single paper face a problematic set of incentives surrounding what makes an interesting publication. Replication efforts that group together a large number of papers have more options, particularly in relation to how that work is distilled in short summaries and media reports: the fraction of a category of papers that proves to be replicable, by some standard, is of interest to readers, no matter whether it is high or low. This kind of multi‐paper exercise can also be combined with other types of analysis. Galiani, Gertler, and Romero (2018) examined hundreds of papers, combined their analysis with a survey of journal editors, and published their analysis in _Nature_ . Camerer, et al. (2016), for example, examined 18 prominent lab‐ experimental economics papers for their results’ reproducibility using a new set of experimental participants, and combined it with predictions of replicability. Eleven (61 percent) of 18 studies’ results were replicated successfully; the paper describing the effort was published in _Science_ . Camerer, et al. (2018
# **7.  Summary and Conclusions**

This paper has extended recent research on satellite-based CO2 measurement to an easily-updated template for tracking changes in CO2 concentration anomalies at local and regional scales. Using observations from NASA’s OCO-2 platform, we develop the template from the data filtering techniques and econometric analysis employed by Dasgupta, Lall and Wheeler (2022). For a large sample of urban areas, we compare alternative trend estimation models and conclude that the template can be constructed from a simple model that estimates trends directly from OCO-2 data that are prefiltered to isolate local concentration anomalies. We also investigate the impact of regional atmospheric circulation on local changes and develop a methodology for identifying urban areas whose changes are independent of regional circulation effects. We present illustrative applications for a long-period trend model and a short-period model that focuses on changes in the most recent year. In both cases we find striking patterns of variation, across regions, within regions, and over time.

We also use our estimation results to compute expected emissions for a large number of urban areas. Then we convert the regression residuals to emissions deviations using information from the EDGAR global database of estimated CO2 emissions. This enables us to quantify the extent to which urban emissions are greater or less than their expected values. Among 1,306 urban areas with populations greater than 500,000, we find a rough balance between cities with positive and negative emissions deviations. In the distribution of percent deviations, we find typically-higher deviations among cities whose emissions are below their expected values.

We conclude with an acknowledgment that even “simple” trend tracking and emissions estimation require software and hardware that are beyond the means of many interested stakeholders. For this reason, the World Bank’s Development Economics Vice Presidency (DEC) has established an open web facility, the XCO2 database,<sup>19</sup> that pre-filters the OCO-2 data and publishes monthly mean concentration anomalies for all terrestrial cells of a 25 km global grid (G25). The website will also
Policy Research Working Paper Series

||Title|Author|Date|Contact<br>for paper|
|---|---|---|---|---|
|WPS1719|Shifting Responsibility for Social<br>Services As Enterprises Privatize in<br>Belarus|David Sewell|February 1997|0. Lawrence<br>32216|
|WPS1720|The Distributionof Foreign Direct<br>Investment inChina|Harry G. Broadman<br>Xiaolun Sun|February 1997|J.Grigsby<br>82423|
|WPS1721|EU Accession of C0entral and<br>Eastern Europe: Bridging the<br>Income Gap|Luca Barbone<br>Juan Zalduendo|February 1997|L. Barbone<br>32556|
|WPS1722|Uncertainty, Instability, and<br>Irreversible Investment:Theory,<br>Evidence, and Lessons for Africa|Luis Serv6n|February 1997|E. Khine<br>37471|
|WPS1723|The Productivity Effects of<br>of Decentralized Reforms: An<br>Analysis of the Chinese<br>Industrial Reforms|Lixin Colin Xu|February 1997|P. Sintim-Aboagye<br>38526|
|WPS1724|Debt Maturity and Firm Performance<br>A Panel Study of Indian Companies|Fabio Schiantarelli<br>Vivek Srivastava|February 1997|B. Moore<br>38526|
|WPS1725|Access to Long-Term Debt and<br>Effects on Firms' Performance:<br>Lessons form Ecuador|Fidel Jararnillo<br>Fabio Schiantareili|February 1997|B. Moore<br>38526|
|WPS1 725|Roads, Population Pressures,<br>and<br>Deforestation in Thailand.<br>1976-89|Maureen Cropper<br>Charles Griffiths<br>Muthukumara Mani|February 1997|A. Maranon<br>39074|
|WPS1727|The Economics of the Informal<br>Sector: A Simple Model and Some<br>Empirical
**Table 7:** _Sensitivity Analysis: Recall Bias_

|Dependent Variable:|||
|---|---|---|
|Infant Mortality (sample)|(1)|(2)|
|Used Survey|-0.0049**<br>(0.0024)|-0.0050**<br>(0.0025)|
|Used Survey_×_Decision Point||0.0006<br>(0.0030)|
|F stat (p value)||(0.2147)|
|Number of Observations|37,850|37,382|
|Number of Countries|44|44|

Notes: All estimations include country by mothers’-birth-year by babies’-birth-year fixed effects. F stat(p value) tests Used Survey+Used Survey _×_ Decision Point=0. Robust standard errors clustered at the country level in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

31