rafmacalaba/datause-encoder-data huggingface dataset:
# **3.1 The Costs of RoO: a decomposition**

> Suppose that a producer in the Philippines wishes to sell a shirt, _X i_ ,  under preferential access in another AFTA member, Thailand.  This shirt is produced with ‘originating’ intermediate goods (i.e. with intermediates  from other AFTA members and from domestic sources), _Z oj_ , but also with inputs from non-originating sources,

_N Z j_ , say from Bangladesh or India. Let _i_ stand for the shirt and _j_ for the intermediates, say textiles. Omit any taxes paid domestically, and label each input with its own price since intermediates are differentiated products. Let _VAi_ represent the payments to labor (and to capital or profits). Then the value of final sales is broken down between payments to value added and to intermediate products: To obtain originating status, intermediate purchases from domestic producers of textiles and from textile producers in the regional partner countries are counted as _O O_ ‘originating’ i.e. _Pj Z j_ counts as regional value-added. Then, unrestricted originating value-added expressed as a percent of unit sale (evaluated at FOB prices in the case of AFTA) is given by the expression: Now assume that to satisfy origin requirements to sell under preferential status in Thailand, the producer in the Philippines is forced to source more originating inputs than he would under optimal circumstances (i.e. in the absence of the PSRO). If we let an “*” denote the initial unconstrained (i.e. optimal) choice, and a “c” a constrained choice, then modeling the effects of a binding value content boils down to modeling the implications of: _C_ In the case of AFTA, ( _vai_ ≥ 40% ) is the uniform criterion used to qualify for originating status (although producers also have the option of using other qualifying requirements, notably in the T&A sector where the alternative PSRO were used because the value-content rule was found to be too restrictive).

Figure 3, adapted from Krishna (2006) shows the costs implications of forcing a producer to use more originating inputs than he would otherwise. Assume a competitive environment with a constant- returns-to- scale technology where the producer who takes his cost-minimizing decision on the basis of given prices. When he is unconstrained in his purchase of intermediates, (i.e. when _z_ ≡ _Z ROW_ / _Z AFTA_ = _z_ * ), his unit costs are given by _c_ = _c_ 0 . When he is constrained (i.e. ( ) _C_ when _z_ = _z_ ), his unit costs are higher and given by _c_ = _c_ 1.

``` 8 ```
# **Box 1: The narrative approach to identification**

Following Blanchard and Perotti (2002), the traditional strategy used to identify fiscal, monetary, and (more recently) reserve requirement shocks has relied on vector autoregression analysis (VAR) together with timing assumptions regarding the dynamics between policy and output. On the fiscal side—using — quarterly data it has been assumed that government spending requires at least one quarter to respond to news about the state of the economy and that active fiscal policy may affect output in the same quarter (i.e., government spending is more “exogenous” or slow-moving than output). The opposite has been assumed on the monetary front (using monthly data). While changes in policy rates are not allowed to have contemporaneous (i.e., within the month) effects on macroeconomic variables, developments in the stance of the economy are allowed to affect monetary policy. Mimicking this monetary identification strategy, several recent papers (e.g., Glocker and Towbin, 2012; Tovar, GarciaEscribano, and Vera Martin, 2012) have analyzed the impact of reserve requirement changes on credit — and economic activity obtaining—in some circumstances some puzzling results. For example, Tovar, Garcia-Escribano, and Vera Martin (2012) find that an increase in reserve requirements increases private credit.

Federico, Vegh, and Vuletin (2013b), rely on the use of Romer-Romer type narratives to identify shocks to reserve requirements.<sup>31</sup> To the best of our knowledge, this is the first instance in this literature in which such an approach has been followed. Using historical documents, including IMF and central banks reports, we classify changes in reserve requirements into (i) endogenous changes, which were mainly motivated by current or projected output fluctuations (i.e., when output growth differs from normal) and (ii) exogenous changes, which were triggered by reasons exogenous to the business cycle, including microprudential factors and financial liberalization. When we then incorporate the exogenous changes in reserve requirements into our VAR analysis, we find that, as expected, higher reserve requirements reduce private credit and output.<sup>32</sup> Our analysis also confirms that endogenous changes in reserve requirements, in turn, respond positively and strongly to output shocks. This striking difference clearly shows the importance of following an identification strategy that is able to isolate policy innovations that are exogenous to the business cycle.

> 31 See, for example, Romer and Romer (2010) and Riera-Crichton, Vegh, and Vuletin (2012) for a discussion of the use of narratives to evaluate the effect of taxation policy, and Romer and Romer (2004) and Coibion (2012) for the case of monetary policy.

> 32 Moreover, past output fluctuations are poor predictors of changes in exogenous reserve requirements changes, supporting our narrative categorization.

26
<!-- Start of picture text --> Average Prices, Millet Groats<br>-<br>(December 1991 August 1992)<br>3 ....... ......................<br>I~~~~~~~~~~~~~~~~~~~~~~~~ C<br>' ;;.. .............. e. . . . .................................................................. ................................<br>Der91 0112B o2/11 02125 03/31 0414 0412 05/12' 0R2 W16 0660 07/14 07=' 011<br>Date<br>..... State Price<br><!-- End of picture text -->

**_55_**
<!-- Start of picture text --> 8<br>ge /<br>c<br>=<br>uv 6<br>i<br>«5<br>=<br>€<br>Y 4<br>[=)<br>a<br>£3<br>cre]<br>2<br>2<br>o<br>=1<br>0<br>0 0 0 111 1 10 0 0 0 0 0 0 0 0 0 0<br>Conflict year (O=no, 1=yes)<br><!-- End of picture text --> <!-- Start of picture text --> 9<br>—xe §<br>£7<br>jal)<br>aoto 6<br>£5<br>call]<br>=><br>24<br>&<br>a)<br>uw<br>oO<br>gv?<br>ou<br>=<br>—~1<br>0<br>Oo 1 0 1 1 1 0 01 1 0 10 1 0 1 1 0 +0<br>Conflict year (O=no, 1=yes)<br><!-- End of picture text -->
# **Figure 8: Share of Households for whom finburden=3 by Income Decile, 2007**

<!-- Start of picture text --> Austria Belgium Cyprus Czech Republic Denmark<br>.8 .8 .8 .8 .8<br>.6 .6 .6 .6 .6<br>.4 .4 .4 .4 .4<br>.2 .2 .2 .2 .2<br>0 0 0 0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Estonia Finland France Greece Hungary<br>.8 .8 .8 .8 .8<br>.6 .6 .6 .6 .6<br>.4 .4 .4 .4 .4<br>.2 .2 .2 .2 .2<br>0 0 0 0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Ireland Italy Latvia Lithuania Luxembourg<br>.8 .8 .8 .8 .8<br>.6 .6 .6 .6 .6<br>.4 .4 .4 .4 .4<br>.2 .2 .2 .2 .2<br>0 0 0 0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Netherlands Poland Portugal Slovak Republic Slovenia<br>.8 .8 .8 .8 .8<br>.6 .6 .6 .6 .6<br>.4 .4 .4 .4 .4<br>.2 .2 .2 .2 .2<br>0 0 0 0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br>Spain Sweden United Kingdom<br>.8 .8 .8<br>.6 .6 .6<br>.4 .4 .4<br>.2 .2 .2<br>0 0 0<br>1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10<br><!-- End of picture text --> Source: SILC - EU Statistics on Income and Living Conditions, 2007 21
32 1993. -Transforming State Enterprises in Poland: Evidence on Adjustment bv Manufacturing Farms.' Brookings Papers on Economic ActiviEy. 1:1993. 213-270.

- to. Brian. Fabrizio Coricelli. and Luis de la Calle. 1990. 'Poland: Macroeconomic Policy in the Second Phase of the Reform Program:. _Mimeo._ Washington: The World Bank (December).

- Laffer. Mark. 1992. "The Polish State-Owned Enterprise Sector and the Recession in 1990. _Compararive Economic SVSrem._ 34. no. 1. Spring 1992.

- cifer. A. (1993). "Discussion". Discussion of Pinto et aiji _(1993)._ Brookings Papen on Econommc Aciivity. 1:1993.

- Wijnbergen. Sweder. 19922. "Economic Aspects of Enterprise Reform in Eastern Europe." In _Finance in rtze International Economy 1992.-_ edited by R. O'Brien. Oxford University Press.

- bster. Leila. 1992. "Private Sector Manufacring in Poland: A Survey of Firms." Indusy Series Paper No. 66. The World Bank Industrv and -Energy Department.

Ilisz. Stnislaw. Henryk Kierzkowski. and Marek O0kolski. 1991. 'Macroeconomnic Policies in Poland in 1990 and 1991." PPRG Discussion Papers. No. 1. Warsaw University.
Policy Research Working Paper 5093

# **Abstract**

This paper uses a rural household survey dataset collected in 2006 and 2008 to investigate the impact of a marketbased land resettlement project in southern Malawi. The program provided a conditional cash and land transfer to poor families to relocate to larger plots of farm land. The average treatment effect of the program is estimated using a difference-in-difference matching technique based on propensity score matching; qualitative information complement the analysis to ensure unobservable characteristics do not bias the findings. As expected, the results show a significant effect on landholdings and agricultural production, with land size increasing and maize production increasing by more than 100 kilograms relative to the control. However, the impacts on food security and asset holdings were mixed. Households that relocated great distances had systematically lower impacts than those households that stayed within their district of origin because they had to adapt to unfamiliar agroecological, cultural, and market environments. Impacts also varied across gender of the household head; femaleheaded beneficiary households increased their productive and consumption assets significantly, while male-headed households increased their asset holdings less so.

This paper—a product of the Corporate, Global and Methods Division , Independent Evaluation Group—is part of a larger effort in the department to evaluate World Bank programs rigorously. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at xdelcarpio@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
(US$43), and showed that only 5 percent of female firms had any paid workers. The most common activities, accounting for 40 percent of the women earning below the median profits, are female-dominated industries of apparel manufacture (sewing) and processed food production sold in local markets. Given this context, our goal was to investigate the effectiveness of business training to increase female labor force participation rates and to raise the income levels of low-earning women already in business. The first step in this process therefore involved putting together samples of these two groups.

# **2.1 Generating a sample**

In selecting the sample we balanced the goals of creating a representative sample with logistical concerns. We chose to sample in the two largest urban areas in Sri Lanka – greater Colombo and greater Kandy.<sup>3</sup> Within each of the two urban areas we selected 5 D.S. divisions in urban and semi-urban areas. We located a training venue in each of the ten D.S. Divisions, thus minimizing the required travel time for project participants. Within each D.S. division we then conducted a door-to-door screening exercise in selected G.N. Divisions.<sup>4</sup> The short screening survey gathered employment information on females aged 25 to 45 living in the household.

For self-employed women, our screening survey identified women who worked more than 20 hours per week in self-employment, were involved in a sector other than seasonal agriculture or fisheries, and had monthly profits of 5000 Rs or less (the median in the general population of female self-employed). We refer to this as our _current business owner_ sample.

The second group of interest was women who were out of the labor force, but who were likely to enter the labor force within the next year. For females out of the labor force and between 25 and 45 years of age, the screening survey asked directly whether the woman planned to enter self-employment in the next year, as well as the nature of the business that she planned to start. As a signal of seriousness of intent, we sampled only women who were able to identify the type of business that they planned to start. Since the ability to participate in full-day business training program was important for the proposed intervention, respondents were also asked about the availability of child care for any children younger than five years of age. Those with children

> 3 The project area includes seven of Sri Lanka’s 25 districts: Colombo, Kalutara, Gampaha, Kandy, Matale, Kegalle and Kurunegala.

> 4 The G.N. Division is the smallest of the four administrative levels in Sri Lanka: Provinces (9), Districts (25), Divisional Secretariat (DS) Divisions (324), and Grama Niladari (GN) Divisions (14,008).

5
|**Table 5: Wald tests of equality of coefficients on opposite sides of the land lease market**||
|---|---|
|**Hypothesis tested (using estimated coefficients given inthe first two columns of table 5)**|**Wald statistic chi2(r)**|
|Symmetry of all coefficients (except woreda dummies), number of restrictions (r)=11|37.20***|
|Symmetry of subset coefficients (resource endowment: labor, land, oxen, assets), r=8|36.60***|
|<br>Owned area|11.2***|
|Owned area=-1, r=2|218.64***|
|Good soil quality|0.57|
|<br>Dependants|0.16|
|<br>Male adult|0.21|
|Female adult|0.99|
|Oxen|22.68***|
|Other livestock|3.08*|
|Rooms|1.94|
|Age|0.06|
|<br>Female headship|0.1|
|<br>Literacy|0.08|
|<br>**Equality of intercept terms**||
|<br>Woreda1<sup>a</sup>|1.13|
|Woreda2|1.72|
|Woreda3|9.31***|
|Woreda4|6.32***|
|Woreda5|14.66***|
|Woreda6|9.49***|

**Note.** * significant at 10%; ** significant at 5%; *** significant at 1%.

> a Woreda1 is the district included in the constant term (the reference category). The intercept term for the other districts is, therefore, the sum of the coefficients of the respective district dummy and the constant term.

24
- Feenstra, R.C. and Hanson, G. H. 1996. "Foreign Investment, Outsourcing, and Relative Wages." In The Political Economy of Trade Policy: Papers in Honor of Jagdish Bhagwati, edited by Feenstra, R. C., Grossman, G.M., and Irwin, D. A. Cambridge, MA: The MIT Press.

- Fajnzylber, P, and W.F. Maloney (2000), "Labor Demand in Colombia, Chile and Mexico, Dynamic Panel Modeling" mimeo, LAC PREM.

- Fajnzylber, P, E. Ribeiro and W.F. Maloney (2000), "Entry and Exit Decisions and Labor Demand," mimeo LAC PREM.

- Freeman, R. B. 1995. "Are our Wages set in Beijing?" Journal of Economic Perspectives 9(3): 15-32.

- Griliches, Z. and Hausman, J. A. 1986. "Errors in Variables in Panel Data." Journal of Econometrics 31: 93-118.

# Hamermesh, D. S. 1993. Labor Demand. Princeton, NJ: Princeton University Press.

- Hanson, G. H. and Harrison, A. 1995. "Trade, Technology, and Wage Inequality." NBER Working Paper 5110.

- Krugmn, P.(1996), _Rethinking International Trade_ (Cambridge: MIT Press).

- Lustig, N. (1992), Mexico: The Remaking of an Economy, (Washington: Brookings Institution)

- Maloney, W. and R. Azevedo (1995), " "Trade Refonm, Uncertainty and Export Promotion: Mexico 1982-1988. Journal of Development Economics, 48:1 67-90.

- Maurice, S. and C. E. Ferguson (1973) "Factor Demand Elasticity under Monopoly and Monopsony," _Economica 11:180-186._

- Ocampo, J.O. and L. Villar (1992), "Trayectoria y Vicisitudes de la Apertura Economica Colombiana," Pensamiento Iberoamericano 21:165-186.

- Pagnagariya, Arvind (1999), "Trade Openness: Consequences for the Elasticity of Demand for Labor and Wage Outcomes." University of Maryland, mimeo.

- Paes de Barros, Ricardo, Carlos Henrique Corseuil and Gustavo Gonzaga (1999), "Labor Market Regulations and the Demand for Labor in Brazil. Mimeo IDB.

- Pissarides, C. A. 1997. "Learning by Trading and the Return to Human Capital in Developing Countries." The World Bank Economic Review 11(1): 17-32.

25
**Table 5.  Small states brain drain by destination**

|<br>|**Skilled emig**<br>|**rants in 2000**<br>**To:**||||
|---|---|---|---|---|---|
|DESTINATION<br>SOURCE|<br>**OCDE**|**USA +**<br>**Canada**|**EU15**|**Australia +**<br>**N. Zealand**|**Others**|
|East Asia and Pacific|76307|31234<br>_41%_|1916<br>_3%_|43053<br>_56%_|104<br>_0%_|
|Latin America and Caribbean|375822|315227<br>_84%_|58780<br>_16%_|1448<br>_0%_|366<br>_0%_|
|Sub-Saharan Africa|44493|12206<br>_27%_|25269<br>_57%_|6554<br>_15%_|464<br>_1%_|
|High-income countries|113555|49201<br>_43%_|48641<br>_43%_|13837<br>_12%_|1876<br>_2%_|
|Total|634100|417289<br>|147626<br>|66107<br>|3079<br>|
|||_66%_|_23%_|_10%_|_0%_|
|<br>|**Skilled emig**<br>|**rants arrived a**<br>**To:**|**fter age 22 i**|**n 2000**||
|DESTINATION<br>|<br>**OCDE**|**USA +**<br>|**EU15**|**Australia +**<br>|**Others**|
|SOURCE||**Canada**||**N. Zealand**||
|East Asia and Pacific|38851|17152<br>_44%_|1391<br>_4%_|20210<br>_52%_|77<br>_0%_|
|Latin America and Caribbean|208565|171624<br>_82%_|35910<br>_17%_|712<br>_0%_|208<br>_0%_|
|Sub-Saharan Africa|29313|8412<br>_29%_|17423<br>_59%_|3096<br>_11%_|170<br>_1%_|
|High-income countries|66301|28013<br>_42%_|29038<br>_44%_|7896<br>_12%_|925<br>_1%_|
|Total|362082|232161|94476|33073|1532|
|||_64%_|_26%_|_9%_|_0%_|
|<br>|**Skilled emig**<br>|**rants in 1990**<br>**To:**||||
|DESTINATION|<br>**OCDE**|**USA +**|**EU15**|**Australia +**|**Others**|
|SOURCE||**Canada**||**N. Zealand**||
|East Asia and Pacific|48797|15718<br>_32%_|736<br>_2%_|32329<br>_66%_|41<br>_0%_|
|Latin America and Caribbean|217056|178872<br>_82%_|36608<br>_17%_|1200<br>_1%_|275<br>_0%_|
|Sub-Saharan Africa|26587|6763<br>_25%_|11173<br>_42%_|8393<br>_32%_|86<br>_0%_|
|High-income countries|81315|33642<br>_41%_|32198<br>_40%_|14472<br>_18%_|452<br>_1%_|
|Total|373885|234995|80748|56488|803|
|||_63%_|_22%_|_15%_|_0%_|

28
# **Revisiting the Trade Impact of the African Growth and Opportunity Act: A Synthetic Control Approach**<sup>_∗_</sup>

Woubet Kassa<sup>_†_</sup> Souleymane Coulibaly<sup>_‡_</sup>

**_JEL Classification:_** F13 F14 F68 O1 O55

**_Keywords_** _:_ Africa Growth and Opportunity Act (AGOA), Synthetic Control Method, Preferential trade agreements, Sub-Saharan Africa, policy evaluation

> _∗_ The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank or the countries they represent. We are grateful to Ana Margarida Fernandes, Emmanuel Lartey, Aaditya Mattoo and Albert Zeufack for their helpful comments and suggestions at various stages of this work. We also thank conference participants at the Center for the Study of African Economies (CSAE), University of Oxford for their comments.

> _†_ The World Bank. Email: wkassa1@worldbank.org

> _‡_ The World Bank. Email: scoulibaly2@worldbank.org
The second panels are the cumulative distributions of wages. These requires no judgements about bandwidths and the vertical "cliffs" indicate where the minimum wage, or multiples, may be influencing. Both the informal and formal wage distributions are plotted in light and dark lines respectively.<sup>7</sup> In each graph, a "piling up" of the probability mass around the minimum wage suggests that the policy has, in effect, forced a change in the distribution.

# _Interpretation_

What is immediately clear is that minimum wages do have the capacity to strongly alter the distribution of wages. Colombia provides an extreme example: the dramatic cliffs in the figures, the low standard deviation, and high skewness (Table 1) likely reflect the impact of the minimum wage rather than the underlying distribution of human capital. Somewhat in contrast to common wisdom, of the Mercosul countries, Brazil and Chile appear to have more binding minimum wages in the formal sector than either the very rigid Argentina, or Uruguay.

More generally, enforcement varies widely across the region and SMWs appear to be somewhat deceptive measures of the efficacy of the minimum wage to affect distribution or a measures of labor market distortion. Chile and Colombia have SMW far below that of Honduras, yet the distortion of the wage distributions in the first two seems dramatic in comparison. This suggests that a country's location in the range of SMWs

> **6** See DiNardo, Fortin and Lemieux (1996) for a thorough treatment of kernel density estimation and Velez and Santamaria (1999) for an application of the CDF to Colombia.

Informal sector is defined in each country either by whether a salaried worker is un-affiliated with social security systems, or works in very small firms ( around 6 or less). The Colombian survey, in particular, has only limited data and therefore shows little difference in means between the two.

8