rafmacalaba/data-use-mentions-extended huggingface dataset:
(2013) find that, as suggested by traditional theory, quota-based protection increases the market power of domestic producers while tariff-based protection does not. Kim (2000) provides similar results based on Korean sector-level data. Antidumping protection, which takes the form of tariffs (or, sometimes, price agreements), has also received some attention, although results are ambiguous.<sup>8</sup> Papers by De Loecker _et al._ (2016) and De Loecker _et al._ (2014) also provide evidence that the markups of domestic firms are affected by tariff reductions. These studies generally use measures of price-cost margins at the firm level to identify market-power effects.

The main problem faced by this literature is that estimating markups over marginal costs requires the use of detailed data on costs and/or strong identifying assumptions.<sup>9</sup> Using market shares as a measure of market power is also problematic, both because one has to define what the appropriate “market” is and because, when studying exporters, the sales of domestic firms are typically not observed. Most of the papers cited above use very detailed firm-level data, allowing for a precise identification of the channels through which trade policy affects markups; but this comes at a cost: these studies are typically limited to a single country—often a single industry— and focus exclusively on domestic producers. Using exchange rate variations to identify price discrimination and therefore market power across destinations has the advantage of requiring data on neither firm costs nor market shares. The idea that useful information on the extent of market power can be generated from price adjustments to exchange rate fluctuations is not new, as it was already present in early work such as Aw (1993), Goldberg and Knetter (1999) or Bernhofen and Xu (2000).<sup>10</sup> Our study, which is close in spirit to those papers, links the literature on PTM with that on trade policy and competition.

We also contribute
level. In Panel A, dependent variable is a binary indicator for providing any transfer outside the household to individuals in the given category in Cols. (1)-(3) and receiving any transfer in Col. (4). Panel B dependent variable is the continuous transfer amount sent in Cols. (1)-(3) and the net amount of transfers sent (transfers sent minus transfers received) in Col. (4). Regressions include strata dummies. N=298 Phase 2 workers. Robust standard errors in parentheses.

In Table 5, we examine treatment effects on transfers to individuals outside of the worker’s household. We focus on Phase 2, since the endline survey asked about transfers in the past 3 months to improve recall—covering only this phase of the study. In Panel A, we examine the extensive margin of making or receiving any transfers. We do not find significant changes in either the likelihood of having made a transfer in the last three months (Cols. 1-3) or the likelihood of having received a transfer in the last three months (Col. 4).

In Panel B, we find that workers increase total outgoing transfers to others (Col. 1, 38%, _p_ =0.049). However, the impact on net transfers, while positive, is statistically insignificant (Col. 4, _p_ =0.32). Given that the endline survey was conducted shortly after the Phase 2 unblock date, this suggestive increase in outgoing transfers may reflect a combination of increased transfers from higher cash-on-hand during the intervention period, as well as redistribution from the unblocked savings. This latter force could reflect both altruism, as well as the likely possibility that _τ_ 2—the social tax rate on the blocked savings account—is not zero. Overall, as intended by our design, our results indicate that the income gains achieved by Private group workers did not come at the expense of lower redistribution to others. Rather, they may have
001|0.004|
||(0.00)|(0.00)|(0.00)|(0.05)|
|ln(Rain)|0.052|0.155|0.017|-1.143|
||(0.06)|(0.17)|(0.10)|(2.14)|
|ln(Temperature)|-0.552|-0.363|0.459|2.242|
||(0.42)|(1.13)|(0.75)|(15.62)|
|ln(Rain CV)|0.161|0.497|0.457*|10.056*|
||(0.14)|(0.43)|(0.26)|(5.73)|
|ln(Temp. seasonality)|-0.022|-0.060|-0.087|-4.483|
||(0.08)|(0.22)|(0.12)|(3.27)|
|Pop. density, 1961|0.016**|0.017|-0.009|-0.076|
||(0.01)|(0.02)|(0.01)|(0.33)|
|Constant|-1.725|-12.714**|-10.57***|-13.192|
||(2.33)|(6.29)|(3.88)|(89.47)|
|First Stage|||||
|ln(dist. to GQ) x Elevation|-0.258**|-0.310***|-0.310***
investment in lifelong learning will be needed to facilitate the training and retraining required for people to meet shifting demands for skills (World Bank 2019c). Improving learning outcomes also requires better measurement and monitoring, more efficient teaching practices, and greater accountability (World Bank 2018c). In LICs, investment in early childhood education can ensure that cognitive and socio-behavioral skills are adequately developed, since addressing deficiencies later in life tends to be much more expensive (World Bank 2019a). To reap the benefits of digital technologies, LICs will require significant investment in human capital.

Reforms to strengthen competition could have synergies with reforms to improve human capital. Firms in EMDEs tend to innovate in marginal process and product improvements rather than engaging in significant technology adoption or new product imitation (Cirera and Maloney 2017). This can partly be attributed to weak managerial capabilities. Better education, especially if combined with more competition, can induce an upgrading of managerial skills that can foster more ambitious innovations.

Finally, better education serves a critical function in reducing inequality both within and between countries. As EMDEs’ workforce grows—while that of advanced economies shrinks—and becomes more skilled, the global economy is expected to benefit and global income inequality is expected to fall (World Bank 2018a).

# 4.4.2 Improve health care

Human capital can be improved by reducing malnutrition and improving health care services. Policy interventions to improve public health, and to ensure and lengthen productive working lives, range widely. Better sanitation and access to clean water would improve public health: 9 percent of the global disease burden may be attributable to unsafe water, inadequate sanitation, and insufficient hygiene (WHO 2008). Improvements in health-care provision can be spurred by well-defined and regularly monitored performance indicators (Bradley et al. 2010). Comprehensive provision of health services has been followed by better health outcomes in countries with higher per capita incomes (Maeda et al. 2014). At the local level, programs targeted at local health service providers or groups of patients
Services Trade Restrictiveness and Manufacturing Productivity: The Role of Institutions,” _Journal of International Economics_ 104(1): 166-82.

- Borchert, I., B. Gootiiz and A. Mattoo, 2014. “Policy Barriers to International Trade in Services: Evidence from a New Database,” _World Bank Economic Review_ , 28(1): 162-88.

- Borchert, Ingo et al. 2019. Applied services trade policy: A guide to the Services Trade Policy Database and the Services Trade Restrictions Index, WTO Staff Working Paper ERSD-2019-14.

- Borchert, I., J. Magdeleine, J. Marchetti and A. Mattoo. 2020. The Evolution of Services Trade Policy since the Great Recession. WTO Staff Working Paper ERSD-2020-02.

Chanda, R. 2009, “Mobility of Less Skilled Workers under Bilateral Agreements: Lessons for the GATS Mode 4 Negotiations”, _Journal of World Trade_ , 43(3): 479-506.

Chanda, R., 2016. “Demographics and Labour Markets: Implications for Mode 4 Trade” in M. Roy and P. Sauvé (eds.), _Research Handbook on Trade in Services._ Edward Elgar.

Drake-Brockman, J., A. Greenidge, J. Lan and Q. Zhao. 2015. “Making the Most of the LDC Services 23
# **Abstract**

Taking price changes from the GTAP (Global Trade Analysis Project) model of world trade, we employ a small open economy computable general equilibrium comparative static model of the Russian economy to assess the impact of global free trade and a successful completion of the Doha Agenda on the Russian economy and especially on the poor. We compare those results with the impact of Russian accession to the World Trade Organization (WTO) on income distribution and the poor. Our model incorporates all 55,000 households from the Russian Household Budget Survey as “real” households in the model. Crucially, given the importance of FDI liberalization as part of Russian WTO accession, we also include foreign direct investment and Dixit-Stiglitz endogenous productivity effects from liberalization of import barriers against goods and foreign direct investment in services.

We estimate that Russian WTO accession in the medium run will result in gains averaged over all Russian households equal to 7.3 percent of Russian consumption (with a standard deviation of 2.2 percent of consumption) with virtually all households gaining. We find that global free trade would result in a weighted average gain to households in Russia of 0.2 percent of consumption, with a standard deviation of 0.2 percent of consumption, while a successful completion of the Doha Development Agenda would result in a weighted average gain to households of –0.3 percent of consumption (with a standard deviation of 0.2 percent of consumption). Russia, as a net food importer, loses from subsidy elimination, and the gains to Russia from tariff cuts in other countries are too small to offset these losses. These results strongly support the view that Russia’s own liberalization is more important than improvements in market access as a result of reforms in tariffs or subsidies in the rest of the world. Foremost among the own reforms is liberalization of barriers against foreign direct investment in business services.

ii
and human capital. In this specification, previous knowledge is used as one of the main inputs for new knowledge. A key feature of this specification is that previous knowledge can be accessed at no additional cost, as if it were a pure public good, for producing new designs of intermediate capital goods. This approach has been taken by many others in the development of endogenous growth models. Although this could be a reasonable assumption as a first approximation to the knowledge function within a closed economy, it might be inappropriate in a global context. Importantly, the first attempt to analyze the predictions of endogenous growth models in the context of an open economy were also made implicitly under the closed-economy assumption. Indeed, in their seminal paper Rivera-Batiz and Romer (1991) (RBR henceforth) developed two approaches for the knowledge function of an economy. In particular, in addition to the stock of (domestic) knowledge, the authors included R&D expenditures as an independent explanatory variable that is unaffected (theoretically) by the stock of previous knowledge. When using the cumulative-knowledge production function, RBR assume that knowledge coming from the domestic and the foreign economy are complements and that both generate positive spillovers of equal magnitude.

This paper generalizes the RBR cumulative-knowledge production function by investigating the impact of several sources of existing knowledge on the generation of new knowledge. That is, we split the sources of the stock of knowledge into domestic, regional or income group, and rest of the world. This approach allow us to test if geographical distance or income per capita gaps are relevant notions of distance for the diffusion of knowledge spillovers across countries. The analysis of product innovation by firms adds another dimension of distance, namely the technological distance between firms, which cannot be assessed using the cross-country patent data.

Thus, the paper is related to the literature on innovation, productivity, and knowledge spillovers. Some contributions, including Bernstein and Nadiri (1989), Jaffe et al. (1993), Audrestsch and Feldman (1996), and Branstetter
._ on MEXDIS I and of _27 bs. pis._ on POLDIS. We can conclude that a 22 The only problem with this methodology is that an estimated VAR is underidentified: an additional restriction must be imposed on the two variable VAR system in order to identify the impulse responses and variance decomposition. The usual restriction is given by the assumption that one error has a contemporaneous effect on both variables, while the other one has a contemporaneous effect only on its own variable. This assumption is said to imply an _ordering_ of the variables.

We assume that _E,_ **_M,_** has a contemporaneous effect on both variables, while C p, does not. This is not an innocuous assumption: the correlation coefficient on the estimated residuals is above 0.7, so the ordering matters. Our assumption is based on several considerations. The first one is that, at least for the first year of our sanple (when the evidence of cointegration is stronger), all the relevant volatility was coming from the news on Mexico and not on Poland. Second, we regressed the residuals from the cointegration relation (the "long run" residuals, LRER in figure 8) on the standard deviation of MEXDIS (MSIG) and on the standard deviation of POLDIS (PSIG): not only MSIG is more significant than PSIG and with the right sign, but the negative sign of PSIG suggests that the volatility of MEXDIS dominates. Finally, and consistently with our belief that Mexico is a leader in the Brady market, the IMF (1995) finds evidence of Granger causality from Mexico to other countries using daily bond prices.
|Ukraine|5.0|7.2|7.8|5.5|3.6|5.1|9.4|11.1|
|Kazakhstan|1.0|4.3|0.4|0.0|0.9|2.8|0.4|14.5|
|Germany|1.3|1.7|2.7|25.0|11.0|5.0|2.7|2.1|
|Greece|1.5|0.0|9.8|0.7|0.1|0.0|0.0|0.4|
|USA|9.7|1.9|3.2|0.7|0.8|0.8|0.9||
|Others|10.6|10.9|11.5|5.1|5.5|5.5|9.0|13.3|
|Total|100|100|100|100|100|100|100|100|

Source: United Nations, Department of Economic and Social Affairs, Population Division, Trends in International Migrant Stock, 2017 Revision

**Table 4 Remittances as percent of GDP (2000-18)**

||2000‐04|2005‐09|2010‐14|2015‐18|
|---|---|---|---|---|
|Armenia|12.9|17.6|18.3|13.1|
|Azerbaijan|2.0|3.6|2.6|2.4|
|Georgia|6.7|8.5|11.2|11.4|
|Kazakhstan|0.3|0.3|0.3|0.3|
|Kyrgyz Republic|2.
partially explained by changes in the composition of employment across sectors, occupations, and the formal or informal status of the worker.

Third, the study provides compelling evidence that the evolution of wage compression across firms is an important driver of wage inequality dynamics among workers in the formal sector. Using matched employer-employee data from Brazil, Costa Rica, and Ecuador, it decomposes the evolution of the wage variance into four components: changes across workers, changes across firms, changes in the assortativity between workers and firms, and a residual. The results show a prominent role of changes in the dispersion of wages across firms.<sup>4</sup> In Costa Rica, where inequality increased, the firm fixed-effects component grew the most. In Brazil and Ecuador, where inequality fell, the firm fixed-effects component fell the most.<sup>5</sup> Moreover, in Brazil and Ecuador, inter-firm differences in pay for similar workers fell, contributing (more than intra-firm dynamics) to less inequality. The important fall in between-firm wage inequality in Brazil and Ecuador is in sharp contrast with results for developed economies where, just like in Costa Rica, between-plant wage inequality has grown over time. Overall, these results highlight the importance of considering firm heterogeneity when examining the drivers of wage inequality in the region.

How could wage inequality decline in Latin America when global forces, in particular skillbiased technical change and job polarization, are increasing the dispersion of wages elsewhere (Autor, Katz and Kearney 2008; Goos, Manning, and Salomons 2009)? This paper assesses changes in employment and wages across detailed occupations in Brazil, Chile, Mexico, and Peru and finds little evidence of job polarization, perhaps with the exception of Chile. Wages expanded rapidly in low-paying occupations relative to high-paying occupations, while technological advances that complement skill intensive occupations predict the opposite. There was no hollowing out in the wage distribution, because occupations with middle and high skill content expanded slowly and at a similar rate, while occupations with low skill
, extending from June through September. The monsoon plays a critical role in determining the success of the kharif (summer season) harvest; rabi (winter) season production depends to a much greater extent on irrigation.

## **4.2 Land values and climate**

Our cross-sectional Ricardian analysis uses reported land values collected from a farm household survey as a measure of _π_ . In principle, the value of land should equal the expected

> 14Ideally, one would want a land productivity panel spanning many decades over which _climate_ has actually changed, and changed to different extents across regions, while the menu of technologies has remained relatively stable. Such data are, at present, unrealistic.

> 15Since the IMD release does not extend past 2003, weather data for our panel analysis are taken from the Center for Climate Research, University of Delaware. Though available at a higher grid resolution (0 _._ 5<sup>_◦_</sup> _×_ 0 _._ 5<sup>_◦_</sup> cells), these data are interpolated using much fewer weather stations than those of IMD.

10
<mark>NBS (2018).</mark> _<mark>N</mark> ational Nutrition and Health Survey (NNHS) 2018 Report on the Nutrition and Health Situation of Nigeria_ . National Bureau of Statistics: Abuja, Nigeria National Population Commission (NPC) [Nigeria] and ICF (2019). _Nigeria Demographic and Health Survey 2018 Key Indicators Report_ . Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF.

Nigerian National Bureau of Statistics (NBS) and World Bank (2019). Basic Information Document Nigeria General Household Survey–Panel 2018/19.

Nigerian National Bureau of Statistics (NBS) and United Nations Children’s Fund (UNICEF) (2017). Multiple Indicator Cluster Survey 2016-17, Survey Findings Report. Abuja, Nigeria: National Bureau of Statistics and United Nations Children’s Fund.

Nwokolo, A. (2019). Terror and Birth Weight: Evidence from Boko Haram Attacks. Draft March 2019. Retrieved 14<sup>th</sup> June 2019: https://novafrica.org/wp-content/uploads/2019/05/Terror_Birth_Weight.pdf <mark>OHCHR</mark> (n.d.). Realisation of the equal enjoyment of the right to education by every girl. <mark>Office of the UN High Commissioner for Human Rights (OHCHR). R</mark> etrieved 27<sup>th</sup> April 2020: <u>https://www.ohchr.org/Documents/Issues/Women/WRGS/ReportGirlsEqualRightEducation.pdf</u> <mark>Pande, R. P. (2003). Selective gender differences in childhood nutrition and immunization in rural India: the role of siblings.</mark> _<mark>Demography</mark>_ <mark>,</mark> _<mark>40</mark>_ <mark>(3), 395-418.</mark
Since 2001, the Ministry of Human Resources and Social Security (formerly Ministry of Labor) has maintained a labor force observation network, which compiles information from both firm and labor force surveys conducted in 159 cities.<sup>2</sup> From this data source, information on vacancies and job seekers may be combined to provide an indication of changing demand for labor. As the data presented in Figure 4, show, the demand for labor dropped sharply, falling from 0.97 to 0.85 from the third to the fourth quarter of 2008. This finding is consistent with information from an Internet-based recruitment company **,** which reported that the growth in vacancies fell off significantly between the third quarter of 2008 and the first quarter of 2009 (Zeng, Cui, and Ding 2009).

The ministry also reports this statistic by gender, based on assumptions about the gender composition of occupations and jobs typically held by men and women. According to variation in this statistic, fewer men than women are typically available for each vacancy: the ratio of vacancies to job seekers is always higher in male-dominated occupations than in femaledominated occupations. With the onset of the financial crisis, however, the percentage drop in vacancies per job seeker was steeper for men than for women (Figure 5), suggesting that the shock hit the demand for male labor harder.

The labor market observation data have two shortcomings: first, the firm survey over-samples firms and vacancies in the formal sector, and the associated labor force survey oversamples longterm urban residents. Second, because the firm surveys are representative of enterprises operating at each period of time, they miss those shocks to employment that result from firm bankruptcy.

Interesting insights on the relationship among firm survival, migrant employment, and the financial crisis are provided by Kong, Meng, and Zhang (2009). This study makes use of a household sampling frame of migrants that was constructed by first sampling enterprises where migrants work and then randomly sampling migrants.<sup>3
, and so on). Instead, in the agricultural module outlined by Reardon and Glewwe (2000), the total days of labor at the household level over the last completed season are collected for each plot and by specific activity. An expanded agricultural module would have the same questions for each household member (as in the LSMSISA).<sup>5</sup> A common feature in these surveys is that labor information is collected from a single interview.

Though it is considered an improvement over surveys with more general labor force questions, the expanded LSMS-ISA agricultural module has several potential drawbacks. First, it is time-consuming to collect this detailed information. Second, the burden on respondents is substantial: respondents are asked to provide information that they may never have considered (for instance, about labor by activity for each plot). Third, there is potential for problems in recall and memory.

# _2.2. What complicates the measurement of smallholder farm labor?_

## **Features of smallholder farming**

> 4 Apart from multitopic household surveys, smallholder information can be collected through specialized farm surveys. These often entail visiting the household at multiple times, particularly those surveys utilizing resident enumerators (for example, agricultural extension agents or other ministry of agriculture staff). However, these surveys typically do not collect details on household farm labor.

> 5 The LSMS-ISA program has been conducted in Burkina Faso, Ethiopia, Malawi, Mali, Niger, Nigeria, Tanzania, and Uganda. See LSMS (Living Standards Measurement Study) (database), World Bank, Washington, DC, http://www.worldbank.org/lsms.

4
Table 4: Additional Heterogeneity Impacts of Trade

|Heterogeneity_Hc_:|Small|Capital|
|---|---|---|
||population|openness|
|Panel A: CIT rate|||
|Trade|-0.053***|-0.063***|
||(0.014)|(0.018)|
|Trade_∗Hc_|-0.034|-0.034|
||(0.054)|(0.079)|
|Coefcient on Trade in_Hc_|-0.088*|-0.094|
||(0.049)|(0.072)|
|Panel B:_ETRK_|||
|Trade|0.357**|0.617**|
||(0.177)|(0.274)|
|Trade_∗Hc_|-0.491|-0.483|
||(0.544)|(0.456)|
|Coefcient on Trade in_Hc_|-0.134|0.133|
||(0.456)|(0.224)|
|Panel C:_ETRL_|||
|Trade|0.169***|0.144|
||(0.061)|(0.158)|
|Trade_∗Hc_|0.145|0.159|
||(0.282)|(0.275)|
|Coefcient on Trade in_Hc_|0.314<br>(0.242)|0.304**<br>(0.139)|

_Notes:_ This table presents results from the heterogeneous IV analysis based on estimating equation (8). The top row denotes the source of heterogeneity _Hc_ , respectively across columns: a dummy for small population size (below 40 million); the Chinn-Ito index of capital account openness (Chinn and Ito