rafmacalaba/datause-encoder-data huggingface dataset:
Finally, our results also suggest that exposing women to positive role models or information that challenges prevailing norms may meet different levels of success depending on the level of autonomy enjoyed by women. In particular, women with low levels of autonomy may require more intensive interventions, consistent with other work which has used information campaigns to change stereotypes. Giné and Mansuri (2011b), for example, find that the response to a voter awareness campaign directed at rural women in Pakistan was most effective among women who had voted in the past and hence had overcome some of the barriers to participation in public life.

# **References**

Akhtar, Shamshad, 2008, “Financial Sector–Ten Year Vision and Strategy.” Presentation at the inauguration of the Development Finance Conference on “Expanding Frontiers of Financial Access in Pakistan” organized by State Bank on the eve of 60th Anniversary of the State Bank of Pakistan, Karachi Banerjee, Abhijit and Esther Duflo, 2008, “Do Firms Want to Borrow More? Testing Credit Constraints Using a Directed Lending Program”, MIT Department of Economics Working Paper No. 02-25.

Beaman, L. Raghabendra Chattopadhyay, Esther Duflo, Rohini Pande and Petia Topalova, 2009, “Powerful Women: Does Exposure Reduce Bias?”, _Quarterly Journal of Economics_ 124(4): 1497-1540.

Bertrand et al., 2010, “What is advertising content worth? Evidence from a consumer marketing field experiment”, _Quarterly Journal of Economics_ , v. 125, issue 1, pp. 263306.

De Mel, Suresh, David McKenzie and Christopher Woodruff, 2009, “Are Women More Credit Constrained? Experimental Evidence on Gender and Microentreprise Returns”, _American Economic Journal: Applied Economics_ , 1(3):1-32.

De Mel, Suresh, David McKenzie and Christopher Woodruff , 2010, “Getting Credit to High Return Microenterprises: The Results of an Information Intervention” mimeo, World Bank.

Evans, Franklin B., 1963, "Selling as a Dyadic Relationship", _American Behavioral_ 22
- Iron supplementation: in discussion rounds, pregnant women are encouraged to take iron supplements that are distributed by health centers

- Bednets distribution for a fee (including a subsidy) and demonstration on their use

- Deworming was offered to all children aged 6 – 59 months.

- Cooking workshops were organized to demonstrate the preparation of nutritious

- foods for the mothers as well as supplements to breastfeeding after six months of age

# <u>2.2 Implementation of the randomized treatment status assignment</u>

As part of the first phase of the PRN, a randomized treatment assignment was implemented in three poor rural regions in order to allow for subsequent evaluation before scaling up to the rest of the country’s rural regions. The implementing NGOs were asked to provide a list of villages in which they had the means and intention to intervene. From the total list of about 1000 villages, 212 villages were randomly chosen in the three regions. Based on these villages, 220 clusters were identified (some villages are large enough to have 2 clusters, and one village had three clusters), and in each cluster up to 20 households were randomly drawn based on the list of households in the village. The nutrition intervention was randomly assigned to half of these villages; the NGOs were asked to schedule services to the other half in a later wave of implementation. They were free to include other villages not among the 212 in the intervention group at any time.

A baseline survey was conducted in April 2004 in all 212 villages, collecting data about the health status of the children, socioeconomic variables of the households these children are residing in, and extensive information about the nutrition and child care practices of the mother. The survey teams administered three questionnaires: a village 5
# **Russian Trade and Foreign Direct Investment Policy at the Crossroads**

# **David Tarr**

# **and**

# **Natalya Volchkova**

# **I. Introduction**

As of June 2009, there were 153 member countries of the World Trade Organization (WTO). Trade among them represented 97 percent of the world's trade turnover, including over 94 percent of the foodstuffs. Russia is the largest economy outside the WTO and—along with Azerbaijan, Belarus, Kazakhstan, Tajikistan and Uzbekistan of the Commonwealth of Independent States (CIS)—is among the 29 countries that were attempting to accede to the WTO in August 2009.

The Working Party on accession of the Russian Federation to the WTO was established June 16, 1993. The WTO Working Party on Russia’s accession comprises about 60 countries, and is the largest such Working Party in the history of the WTO. By the spring of 2007, Russia has successfully concluded bilateral agreements with all the members of its Working Party who sought a bilateral except Georgia.<sup>3</sup> The focus now is on the multilateral phase of the negotiations. Considerable progress on the multilateral issues was made so that by mid-2008, only three issues remained to be resolved; but these three issues remained on the table in mid-2009.

During the first Administration of President Vladimir Putin, Russia actively sought membership in the WTO, and this was seen as part of a strategy of an open economy model of economic development. As we discuss below, however, in recent years Russia, in its efforts to diversify the economy away from energy and raw material dependence, has employed several industrial policy and import-substitution-industrialization measures. We discuss why we believe that Russia’s trade and foreign direct investment policies for the future are at a critical crossroads.

In section II, we summarize the estimates of what Russia will get from WTO accession and why. WTO accession is a long process--as mentioned Russia has been negotiating its accession since 1993. The Russian Duma has already passed into law about 42 significant packages of legislation to conform to WTO requirements,<sup>4</sup> and will implement selected other commitments on an agreed schedule up to several years after its actual accession. The studies mentioned below quantitatively 3 Georgia earlier had agreed to a bilateral agreement on Russian WTO accession but has withdrawn from that agreement.

4 During the first Administration of President Vladimir Putin, the chief negotiator for WTO accession of the Russian Federation prepared a matrix of 42 packages of legislation that he needed to have prepared and passed by the Russian Duma in order to conform to WTO accession requirements.

2
10 much in the education of daughters as in sons, this equation should be estimated separately for males and females to allow the a coefficients to<sup>vary</sup> between the sexes.

We estimate demand for schooling for two samples of the Peru Living Standards Survey (PLSS): a sample of adults aged 20-59,§/ and a sample of youths aged 5-19. For the adult sample we examine the determinants of the highest level of schooling completed; for the youth sample we explain school enrollment or participation.

The explanatory variables X include birth cohort, parental background, and community characteristics. Birth cohort reflects changes in aggregate conditions during different periods. They serve as a crude measure of shifts in the labor market, changes in the economy, or reforms in education that have affected school availability. Because the effects of these events are confounded in the estimates of a, the results are illustrative and meaningful only if they are linked to historica]. events. Early in our study we found strong cohort differences. Rather than simply measure these effects as intercepts, we estimated the equation separately for six birth cohorts. For the adult sample, each group corresponds to a five-year period (except for the earliest and most recent periods).2 Since the youth sample spans a much Although 23 percent of those aged 20-24 were still enrolled in school when the data were collected, the proportion is much higher at younger ages.

_1_ Those born in 1925-39 were grouped together because there were fewer observations for the oldest cohorts, and the lack of data prior to 1950<sup>makes</sup> it impossible to link the educational experiences of this group to historical events.
spillovers from the commercial farms included here to those in flowers or high value vegetables and to those from investments higher up in the agro-processing value chain; and (iii) analyzing effects of large farm establishment on input and output prices as an alternative indicator that could also clarify channels through which some of these effects are transmitted.

The paper is structured as follows: Section two motivates by discussing large agricultural investment in Ethiopia and presenting our methodology. Section three introduces the data and provides evidence on differences in performance between large and small farms, changes in smallholder productivity over time, and changes in spatial proximity between small and large farms over time due to new farm establishment. Section four presents results with respect to input use and yields, labor market participation, and resilience to climatic shocks. Section five concludes by summarizing implications for policy and future research.

# **2. Motivation and methodological considerations**

There is little doubt that growth of smallholder agriculture is critical for poverty reduction in Ethiopia. Yet, to fully exploit its land endowments and generate spillovers for smallholders, the country also aimed to attract agricultural investors, based on the premise that doing so could help local smallholders. To test for spillovers from such investment, we argue that physical proximity, measured by either the distance between smallholders and the next large farm or total large farm area cultivated in smallholders’ vicinity, can be used as a proxy. Data from 11 years of a national smallholder survey as well as the universe of large farms and their evolution over time can provide a basis for doing so in Ethiopia.

# **2.1 Large-scale land investment in Ethiopia**

Ethiopia is one of the poorest countries in Africa and the country’s highlands are among the most densely populated regions in Africa. Land constraints are a key determinant of poverty (Jayne _et al._ 2014). After 1990, a strategy of market liberalization and agriculture-led industrialization focusing on small-scale producers was adopted. In the past, the country regularly relied on food aid to meet food needs in the face of droughts (Dercon 2004). Yet, investment on land not fully utilized is identified as a strategic priority in the government’s Growth and Transformation Plan. This decision to actively seek out large land-based agricultural investment implied that Ethiopia attracted interest by the global ‘land rush’ debate. Historically experience with large farms in Ethiopia has not been positive: Before 1974, subsidies were used to attract commercial investment for cash crops production in so-called ‘model farms’. But this was often associated with tenant evictions and little employment generation with at best mediocre productive performance.<sup>1</sup>

> 1 Although yields were above those by peasants, these farms’ efficiency and contribution to national agricultural output (2%) remained low (Abebe 1990). After the 1974 revolution, most of these were converted into state farms for food production.

4
# **References:**

Akyeampong and Fofack (2012a). ―The Contribution of African Women to Economic Growth and Development: Historical Perspectives and Policy Implications—Part I: The Precolonial and Colonial Period.‖ World Bank Policy Research Working Paper No. WPS6051.

Akyeampong and Fofack (2012b). ―The Contribution of African Women to Economic Growth and Development: Historical Perspectives and Policy Implications—Part II: The Post-Colonial Period.‖ Forthcoming, World Bank Policy Research Working Paper.

Artadi, V. E., & Sala-i-Martin, X. (2003). The economic tragedy of the 20th century: growth in Africa. National Bureau of Economic Research Working Paper No. 9865.

Baliamoune-Lutz Mina and Mark McGillivray (2009). ―Does Gender Inequality Reduce Growth in SubSaharan Africa and Arab Countries?‖ _African Development Review_ , Vol. 21, No. 2, pp.224-242.

Barro Robert and Lee J. W. (1996). ―International measures of schooling years and schooling quality.‖ _American Economic Review_ , Vol. **86** (2), pp. 218-223.

Bayraktar Nihal and Hippolyte Fofack (2011). ―Capital Accumulation in Sub-Saharan Africa: Incomegroup and Sector Differences‖, _Journal of African Economies_ , Vol. 20, Number 4, pp. 531-561.

Boserup Esther (1970). Woman’s Role in Economic Development. London: George Allen and Unwin Ltd, 1970.

Cagatay N. and S Olzer (1995). ―Feminization of the labor force: the effects of long-term development and structural adjustment‖, _World Development_ , 23 (11) 1883-1893.

Charmes Jacques (1998). ―Informal Sector, Poverty and Gender: A Review of Empirical Evidence.‖ Background paper for World Bank, World Development Report 2000. Washington, D.C.

Collins Susan and Barry Bosworth (1996). ―Economic Growth in East Asia: Accumulation versus Assimilation.‖ Brookings Papers on Economic Activity, Vol. 1996, Issue 2 (1996), 135-191.

Devarajan Shanta and Sudhir Shetty (2010). ―Africa: Leveraging the crisis into development takeoff.‖ _Economic Premise_ , September 2010 (30). The World Bank.

Dollar David and Gatti R. (1999). ―Gender Inequality, Income and Growth: Are Good Times Good for Women.‖ Policy Research Report on Gender and Development, Working Paper Series No. 1.

Easterly William and Ross Levine (1997). ―Africa Growth Tragedy: Policies and Ethnic Divisions.‖ _Quarterly Journal of Economics,_ Vol. 112, No. 4.

Esteve-Volart, Berta (2004) _Gender discrimination and growth: theory and evidence from India._ Discussion Paper. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.

Farré L. and Vella F. (2007). ―The Intergenerational Transmission of Gender Role Attitudes and its Implications for Female Labor Force Participation.‖ IZA Discussion Paper No. 2802.

Fofack (2012). ―A Model of Gendered Production in Colonial Africa and Implications for the PostColonial Period.‖ Forthcoming World Bank Policy Research Working Paper.

21
being targeted (i.e., “targeted imports”) by each economy’s new and subsequent investigations since 1Q 2008; the targeted imports as a share of the country’s total 2007 imports; the targeted imports deriving from China as a share of the total targeted imports, and the targeted imports deriving from China as a share of the country’s total imports from China. We construct this table for 12 of the largest WTO economies and users of these trade remedy instruments – four developed and eight developing countries.

**Table 4. The Size of Imports under Attack by the use of Trade Remedy Initiations during 1Q 2008 - 1Q 2009**

|**Importing Country**|**Value of 2007**<br>**imports for products**<br>**facing new**<br>**investigation during**<br>**2008-1Q2009**|**Investigated**<br>**products as a**<br>**share of**<br>**country’s 2007**<br>**total imports**|**Investigated imports**<br>**from China as a**<br>**share of all**<br>**investigated imports**|**Investigated imports**<br>**from China as a**<br>**share of all imports**<br>**from China**|
|---|---|---|---|---|
|Total|$28,977,070,131|0.0045|0.5889|0.0164|
|**Developed Economies**|||||
|EC|$8,032,246,785|0.0041|0.3983|0.0101|
|U.S.|$7,458,154,471|0.0037|0.9032|0.0198|
|Canada|$852,235,098|0.0022|0.9160|0.0218|
|Australia|$95,253,092|0.0006|0.7643|0.0030|
|**Developing Economies**|||||
|China|$6,183,277,841|0.0064|na|na|
|India|$3,943,953,974|0.0180|0.4749|0.0762|
|Turkey|$1,383,230,509|0.0081|0.1452|0.0152|
|Brazil|$540,548,035|0.0044|0.5787|0.0248|
|Argentina|$315,794,401|0.0070|0.5221|0.0324|
|Pakistan|$108,991,018|0.0033|0.5405|0.0141|
|Mexico|$55,581,511|0.0002|0.3106|0.0006|
|South Africa|$7,803,396|0.0001|0.7216|0.0007|

Sources: Product level (6-digit HS codes) for AD, CVD, CSG and SG investigations for these countries obtained from the _Global Antidumping Database_ and matched to 6-digit HS Comtrade 2007 import data available via WITS. Intra-EC trade is excluded.

Not surprisingly, table 4 first reveals that the two economies with the largest _levels_ of imports potentially affected by the remedies are the EC ($8.0 billion) and the U.S. ($7.5 billion). However, the _relative_ importance of the targeted imports is fairly small, as only 0.4 per cent of 2007 imports in these 13
Figure 4: CHB indexes by sector <!-- Start of picture text --> Goods Services<br>0 2 4 6 8 10 0 2 4 6 8 10<br>Private CHB (in logs) Private CHB (in logs)<br>45 line<br>10<br>10<br>8<br>8<br>6<br>6<br>4<br>4<br>Government CHB (in logs) Government CHB (in logs)<br>2<br>2<br>0<br><!-- End of picture text --> To better appreciate differences across public and private markets as well as heterogeneity across countries, Table A2 in the Appendix reports the values of the estimated CHB indexes for goods. Home bias in government procurement is on average 35% higher than home bias in private markets throughout the period. Looking at the average CHBs throughout the period, some differences emerge across countries. Similarly to what Anderson and Yotov (2010a) find for total trade, CHB is massive for small countries like Cambodia, Cyprus, and Brunei. This is because these countries naturally trade a lot with other countries and thus a high share of their income goes through bilateral trade barriers around the world, driving up the multilateral resistance terms. At the other end of the spectrum, CHBs are the lowest for large countries such as the U.S., Japan and China. While governments are more home biased than firms in their purchases of goods, their CHBs have declined more strongly. Only 22 out of 62 countries in our sample experienced an increase in government home bias, whereas CHBs in private markets went up for 32 countries. On average, home bias in government procurement of goods is 10 percent lower in 2015 relative to 1995. In private markets, the average home bias went up on average by 15 percent.

Table A3 in the Appendix reports estimated CHBs for services. As for goods, government – procurement in services is more home biased than services purchases by private firms on average, government CHBs are 18 percent higher than private CHBs. Between 1995 and 30
||||||pollution is unchanged in<br>non-traffic areas|
|---|---|---|---|---|---|
|Davis (2008)|Mexico|1986-1993|Air quality using hourly air<br>pollution records from<br>monitoring stations|Regression<br>discontinuity|Driving restriction led to<br>worse air quality since the<br>policy incentivized drivers<br>to circumvent the<br>restriction by purchasing a<br>second vehicle, which<br>tended to be older and<br>dirtier.|
|Viard & Fu<br>(2015)|China|2007-2009|Air pollution (both an<br>aggregate and individual<br>monitoring-station level),<br>hourly measure of TV<br>viewership by different<br>categories of Beijing<br>resident|Regression<br>discontinuity and<br>Difference-in-<br>differences|The every-other-day<br>driving restrictions led to a<br>19 percent reduction in air<br>pollution and that the one-<br>day-a-week restrictions led<br>to a 7 percent reduction.|
|Zhang et al<br>(2017)|Colombia|1997-2009|Air pollution (hourly) and<br>air quality|Regression<br>discontinuity|Emergency room visits<br>declined as a result of<br>driving restriction policy.|
|Xu et al (2017)|China|2006-2010|Resale housing transaction<br>(WoAiWoJia), location<br>attributes for residential<br>complex, travel times from<br>each residential complex to<br>CBD|Hedonic price<br>regressions|Commuters in have mainly<br>resorted to public transit<br>instead of the purchase of<br>the second vehicle to meet<br>their travel demand.|
|Li (2018)|China|2008-2012|monthly vehicle sales by<br>model (vintage-nameplate),<br>vehicle characteristics of<br>each model, income<br>distributions, household<br>surveys|Structural econometric<br>model|The lottery system leads to<br>a large welfare loss from<br>misallocation.|

47
institutional hypothesis, it does not appear to be the principal explanation for Mexican earnings inequality.

The SBTC hypothesis links earnings inequality to technology that raises relative demand for skilled labor. Cragg and Epelbaum (1996) find that, given different labor supply elasticities, the primary source of Mexican wage inequality is a skill-biased demand shift rather than skilluniform demand growth. Meza (1999) also investigates the Mexican labor market, and finds that intra-industry demand shifts toward a more educated labor force explain unskilled labor wage decreases better than interindustry demand shifts. The World Bank (2000) also shows that demand increases for a more educated labor force within the economic sectors explain the increase in their premium when compared to the demand shifts for less educated workers between economic sectors. Acosta and Montes (2001) show that there is a constant increase on skill premia during the 1987-1993 period, but there is a deceleration during the 1994-99 period and a decline after 1997. These authors contend that the former may be caused by between industry differences.

Batra and Tan (1997) study the SBTC hypothesis as a plausible explanation of wage inequality using firm-level data for Colombia, Mexico, and Taiwan (China). They find that technology's impact on wages is greatest for skilled workers and lowest for unskilled workers, thereby supporting the SBTC hypothesis. In this hypothesis, skilled workers become more efficient in jobs traditionally performed by unskilled workers (Johnson 1997).

# 3. **Technology's influence on wages and employment**

To determine whether the technology of Mexican firms influences their skill demand, we estimate determinants of each skill group's share of total wages. In this fixed-effects model, we use a modified first-differencing to eliminate firm-specific error. For a cost minimizing firm, the following equation models technology's influence on wages: _Wii, = AS In VA4j, + 82 In K;,_ **+ ,63** In _Rj,_ **_+ ,B4_** _InTFPi,_ **_+ ,B5_** _InUR, + Zi, (1)_ where: 7
# **1. Introduction**

In their seminal paper, Basu and Van (1998) proposed the “luxury axiom” that children only work when their families are unable to meet their basic needs. This axiom suggests a strong linkage between child labor and poverty, and has been supported by many cross-sectional studies (see, for example, Maitra and Ray(2002) and Ersado(2005), and panel data studies, such as Edmonds (2005)). However, other studies have shed doubt on this axiom by suggesting a more nonlinear relationship between poverty and child schooling/work decisions. For example, Bhalotra and Heady (2003) found a “wealth paradox”- children in land-rich households are more likely to work and less likely to attend school than children in land-poor households. Swaminathan (1998) showed that in Gujarat, India, wage employment increased among children with economic growth. Similar trends were also found in other Indian states (Kambhampati and Rajan 2006).

Pakistan presents a particularly interesting case in studying the relationship between wealth and child labor and schooling. Pakistan experienced strong economic growth from 1998 to 2006, despite a severe drought in 2001 and an earthquake in 2004. Economic growth has translated into higher household incomes and lower levels of poverty. However, the implications of economic growth during this period on child labor and schooling are less known. That said, however, if we assume that poverty is a key barrier for school enrollment, then it follows that school enrollment rates should have increased. Conversely, if we assume that economic growth induces higher demand for child labor, then the incidence of child labor should have risen.

The main objective of this paper is to examine the association between wealth and child labor and schooling in Pakistan in the context of economic growth from 1998 to 2006. Child labor and schooling, however, are only two dimensions of child activities. In Pakistan, another 2