rafmacalaba/datause-encoder-data huggingface dataset:
- Bown, Chad P. and Mark Wu. 2014. “Safeguards and the Perils of Preferential Trade Agreements: Dominican Republic - Safeguard Measures.” World Trade Review 13(2): 179-227.

- Brainard, Lael. 1994. “Last one out wins: trade policy in an international exit game.” International Economic Review 35(1): 151-72.

- Brander, James A. 1995. “Strategic trade policy.”In Handbook of International Economics, edited by Gene M. Grossman and Kenneth Rogo¤, 3: 1395-1455. Amsterdam, NL: North-Holland.

- Brander, James A. and Barbara Spencer. 1981. “Tari¤s and the extraction of foreign monopoly rents under potential entry.” Canadian Journal of Economics 14(3): 371-89.

- Brander, James A. and Barbara Spencer. 1984. “Tari¤ Protection and Imperfect Competition.”In Monopolistic Competition and Product Di¤erentiation and International Trade, edited by Henryk Kierzkowski, 194-206. New York: Oxford Economic Press.

- Brander, James A. and Barbara Spencer. 1985. “Export subsidies and market share rivalry.” Journal of International Economics 18(1-2): 83-100.

- Brock, William A. and Stephen P. Magee. 1978. “The Economics of Special Interest Politics.” American Economic Review 68(2): 246-250.

- Broda, Christian, Nuno Limão, and David E. Weinstein. 2008. “Optimal tari¤s and market power: the evidence.” American Economic Review 98(5): 2032-65.

- Bronckers, Marco and Naboth van den Broek. 2005. “Financial Compensation in the WTO: Improving the Remedies of WTO Dispute Settlement.” Journal of International Economic Law 8(1): 101-126.

- Brou, Daniel and Michele Ruta. 2013. “A commitment theory of subsidy agreements.” BE Journal of Economic Analysis & Policy 13(1): 239-270.

- Cadot, Olivier, Jaime de Melo and Marcelo Olarreaga. 1999. “Regional integration and lobbying for tari¤s against non-members.” International Economic Review 40(3): 635-57

- Caliendo, Lorenzo and Fernando Parro. 2015. “Estimates of the trade and welfare e¤ects of NAFTA.” Review of Economic Studies 82(1): 1-44.

- Calvo-Pardo, Hector, Caroline Freund, and Emanuel Ornelas. 2011. “The ASEAN Free Trade Agreement: Impact on Trade Flows and External Trade Barriers.”In Costs and Bene...ts of Economic Integration in Asia, edited by Robert J. Barro and Jong-Wha Lee, 157-186. Oxford, UK: Oxford University Press.

- Caplin, Andrew and Kala Krishna. 1988. “Tari¤s and the most-favored-nation clause: A game-theoretic approach.” Seoul Journal of Economics 1(3): 267-89.

- Carmichael, Calum M. 1987. “The control of export credit subsidies and its welfare consequences.”Journal of International Economics 23(1-2): 1-19.

105
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Graphs by Shock
-116-

-----------------------------------------------------------------------

__--

**TABLE A.3**

U.S. Retail Prices in 1975 for 4 Cylinder and 6/8 Cylinder Cars

|Model|Retail value<br>(1000 USS)|Number produced|Retail price<br>(US$)|
|---|---|---|---|
|a) 4 cylinder cars<br>Vega<br>Pinto|193,882<br>163,506|540,155<br>477,274|2,786<br>2,919|
|Bobcat|60,706|193,591|3,189|
|Astra|55,805|158,542|2,841|
|Monza|82,960|302,638|3,648|
|Mustang|93,727|330,763|3,529|
||650,586|2,002,963||

|Average|retail price:|2,002,963 - 650,586=|S 3,079|
|---|---|---|---|
|b) 6/8 cylinder cars||||
|Cutlass|363,814|1,361,756|3,743|
|Granada|336,842|1,245,642|3,698|
|Nova|274,521|850,741|3,099|
|Chevelle|269,967|919,777|3,407|
|Monte Carlo|266,541|1,132,533|4,249|
|Century|212,948|812,397|3,815|
|Cadillac|193,444|1,583,146|8,184|
|Ford|191,400|909,724|4,753|
|Dart|161,567<br>|532,686<br>|3,297<br>|
|Camaro|156.406|553,677|3,540|
|||2,427,450|9,902,079|

# Average retail price: 9,902,079 - 2,427,450 = S 4,079

Source: All 4 cylinder cars produced in 1975 are listed in part a) of the table, whereas part b) refers only to a sample. The 10 models listed in part b) are the 10 best-selling models in 1975 as shown in Automotive News, 1975 Almanac Issue for which retail prices could be identified from the same source. Some of the "models" listed in Automotive News are generic names such as Buick or Oldsmobile for which no single or representative retail price is available. These models had to be excluded from the "best-selling" list. All prices shown are those for the cheapest model-type available. This is usually a 2-door Sedan-Coupe.
**Table 5 Producer prices in Kenya**

> _(percentoge of inpor/export pariry)_

|_Product_|_1_984-6|_1_99_-92_|
|---|---|---|
|Maize|||
|Percent of import panty|73.2'|69.9|
|Percent of export parity|1 55,7|28.8|
|Coffeeb (percent of export price)|9 1.3|89.5|
|Teab (percent of export prices)|84.4|88.6|

a Figure for 1 983, since there were no exports in 984 b. These are average prices. Small holders obtained about 80 percert of the price obtained by estates, because of differences in quality, and, in the **-wse** of coffee growers, deductions by the co-operatives Source World Bank data and estimates by Gurushri Swamy

**Table 6 National cereals and produce board operations**

|_Item_|1983-84|_1991-92_|
|---|---|---|
|Producer price of maize (KSh/ton)<br>|144|300|
|Price to millers (KShAton)<br>|208|3 59|
|Gross margin/producer<br>price (percent)<br>|53.5|19.7|
|Natonal cereals and produce<br>|||
|board deficits (K£: millions)'<br>|12.8|70.9|
|Deficit/current govemment<br>expenditures<br>|I .3|2.3|
|Deficit per ton handled<br>(KLper ton)|1 1.4|74.3|

a. Before finance charges b. Sales and purchases Source: World Bank and Egerton University data, _Proxeedings_ of Conference on _Maize_ Supply and _Morketing,_ June 1 99, and estimates by Gurushri Swamy 66
Policy Research Working Paper 9026

# **Abstract**

Global consumers, international brands, and governments in producing and outsourcing countries aim to improve working conditions in global value chains, but uncertainty exists about what is the best approach. This research uses firm-level data from the International Labour Organization–International Finance Corporation Better Work Vietnam program to assess the relationship between transparency on working conditions and firm compliance in the apparel sector in Vietnam between 2010 and 2018. It exploits a change in the policies of Better Work Vietnam when, in 2015, the program announced the launch of a new public disclosure program that would see factories’ names made publicly available along with their compliance (or lack thereof) with certain “critical issues.” The paper first examines which firm characteristics correlate with reductions in noncompliance rates over time, and then examines the impact of the public disclosure policy on compliance rates and firm dropout using different empirical techniques. It finds that while continued participation in the Better Work Vietnam program has the strongest effect on changes in firm compliance with labor standards over time, public disclosure is also associated with increased compliance, with stronger effects in some compliance points, including occupational health and safety, work time, and child labor. There is some evidence of increased dropout, but no evidence of firms only making progress on the critical issues is found. The research findings suggest that public disclosure within global value chains matters for firm behavior.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at chollweg@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
appears to lead to more reliable results than asking household-heads about deaths in the household during the preceding year. Moreover,<sup>a</sup> smaller sample size is possible, because the respondent can<sup>be</sup> questioned about the survival of more than one relative over a longer period of time.

The sibling survivorship method has been adapted to estimate the rate of mortality from maternal causes (Graham et al, 1988), and Timmaeus and Graham (1988) suggest that indirect methods could be similarly adapted for the estimation of mortality rates from<sup>other</sup> causes. There are two major difficulties with this approach:

- (i) The indirect methods involve questions concerning deaths<sup>to</sup> relatives that occurred at any time since they reached adulthood, implying a long recall period for many of the deaths.<sup>A-short</sup> recall period is likely to be needed, however, for the reliable retrospective diagnosis of most causes of death.

- (ii) The indirect methods involve questions about relatives that may have lived in different houspholds from the respondevts, who may therefore know little or nothing about the circumstances of death. It is probable that only respondents who lived in close proximity to the deceased prior to the death are able to give adequate information about the cause of death.

Thus the factors that lead to advantages in the use of indirect methods for the study of the level of adult mortality, are obstacles<sup>in a study</sup> of cause-specific mortality.

- Nevertheless, the basic approach of questioning all household

- members about deaths-to their relatives still has advantages for<sup>a</sup> single-round survey of causes of death. Firstly, it obviates the difficulties mentioned above connected with the reformation of families following a death. Secondly, the head of household may often be less able than a specified relative to provide detailed information about the death.

This suggests that a fruitful approach might be to question<sup>all</sup> adult members of each household concerning deaths of specified relatives, but to restrict cause of death questioning to deaths that satisfy a number of additional criteria relating to the<sup>time at which</sup> the death occurred, and the proximity of residence of the deceased and the respondent at the time of death. In this way, the same<sup>survey could</sup> be used both to provide estimates of overall levels of adult mortality, and to estimate the proportions of deaths attributable to different causes. This possibility, and various problems and biases that may result, are discussed in the sections that follow.

# 3.2.2 Selection of respondents

Respondents should be restricted to those aged 15 years or more, as children are unlikely to be able to provide reliable information about the symptoms and circumstances relating to an adult death.

In principle, it would be possible to ask each respondent<sup>about</sup> the survival of just one type of relative. The spouse might<sup>be the most</sup> 13
# **Box 1 – Constructing alternative proxies of regulatory environment: Principal Component Analysis using Doing Business data**

The PCA indices are linear combinations of Doing Business sub-indicators, where each sub-indicator is multiplied by an optimal weight that best accounts for the variance of the indicators. For example, the principal components analysis index for business entry is calculated through the following equation: _Business Entry index = w0*(Starting a Business) + w1*(Registering Property)+ w2*(Closing a Business),_ where the weights w0, w1, and w2 are the weights that lead to the greatest variance. All principal components analysis indices are coded so higher numbers indicate less complex regulation.

**Figure 4: PCA indicator (All_DB):2003-2008**

<!-- Start of picture text --> 100<br>Bulgaria<br>Czech Republic<br>90 Denmark<br>Estonia<br>France<br>80<br>Germany<br>Hungary<br>70 Italy<br>Latvia<br>Lithuania<br>60<br>Netherlands<br>Poland<br>Romania<br>50<br>Slovakia<br>Slovenia<br>40 Spain<br>2003 2004 2005 2006 2007 2008<br><!-- End of picture text --> _Note: Authors’ elaboration based on DB data_ The results of estimating Eq(2) are given in Table 4. Consistent with the previous set of results at the country level, labor productivity growth in less productive sectors is positively influenced by the speed at which productivity grows in the same sectors in the best performing countries. In addition, the coefficient of productivity gap is, again, always negative.

11
# **3.5. Landslide susceptibility mapping under factor weight uncertainty**

In the last (seventh) step of the proposed approach, sensitivity analysis is conducted around road susceptibility to landslides. Weight values are randomly selected within the weight range computed in the sixth step of the framework, with all values within the range equally probable. We conducted 80 random weight draws for this case study to cover the weight uncertainty range determined in the sixth step. The randomly selected weights are used to overlay the reclassified factor layers generated in the first step. The resulting composite layer represents the Landslide Susceptibility Index (LSI). Equation 2 describes how the reclassified factor layers are overlaid.

Where LSI is the Landslide Susceptibility Index, Wi is the weight of the factor number i, Si is the score layer of the factor number i, and n is the number of factors considered. The resulting LSI layers were classified into very low, low, moderate, high, and extremely high classes. Table 4 reports the LSI classes used in this study. These classes were obtained from CEGIS; CEGIS created this classification scheme for a previous landslide susceptibility assessment in Bangladesh. After classifying the susceptibility layer, the length of local roads and highways passing through each landslide susceptibility class is calculated in addition to the percentage lengths of roads and highways within each class.

Table 4 Landslide Susceptibility Index classes adopted in this study.

|**Landslide susceptibility**<br>**class**|**Landslide Susceptibility Index**<br>**(LSI)**|
|---|---|
|Very low|0 ≤ LSI ≤ 2|
|Low|2 < LSI ≤ 4|
|Moderate|4<LSI ≤ 5|
|High|5<LSI ≤ 6|

18
**in the terms of trade,** our estimated effect, associated with a coefficient of 7.76 is in between those of C-E-L (5.66) and B-SM ( 11.0).

These comparisons show how sensitive the coefficient estimates are to the estimation procedure and to time periods. We believe our procedure is preferable to that of B-SM because of likely correlation between country effects and the righthand side variables, and preferable to C-E-L for our purposes because of the inclusion of the reform-relevant last 8 years (1985-93). We acknowledge some concern about the stability of the relationships we are estimating. This instability is reminiscent of the results by Levine and Renelt (1992) about the sensitivity of coefficients to regression specification. As in Levine and Renelt, however, the instability comes about because of difficulty in separating out effects of different policies; the estimated aggregate effects of policy packages are more stable than the estimated effect of each policy in isolation.

# _3. Validity of the instruments_

As explained in section II, the validity of lagged values of income and the explanatory variables as instrments is crucial to the consistency of the GMM estimator. According to the Sargan and serial-correlation test statistics presented in Table 3, our econometric model specification cannot be rejected. In fact, in the regression that includes investment as an explanatory variable, the p-value for the Sargan test is 0.59, and that for the second-order serial correlation test is 0.67. When investment is excluded, the p-value for the Sargan test, 0.41, is lower but still above standard significance levels, and the p-value for the second-order serial correlation test, 0.64, clearly supports the assumption of lack of serial correlation in the growth-regression error terrm<sup>0</sup> lOAs mentioned in a previous footnote, the hypothesis of no first-order serial correlation in the differenced residual is strongly rejected, thus eliminating the possibility that the level residual follow a random walk.

_15_
Table A2: Bilateral difference in corruption

|_Dependent _|_Variable:_||||Migratio|n Flows||||
|---|---|---|---|---|---|---|---|---|---|
|||WG|I CC|WGI|GE|C|PI|IC|RG|
|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Diference <br>Diference|(_o_ - _d_) in WGI CC <br> (_o_ - _d_) in WGI GE|0.25*** <br>(0.01)|0.32***<br>(0.01)|0.37*** <br>(0.01)|0.48***<br>(0.01)|||||
|Diference|(_o_ - _d_) in CPI|||||0.26*** <br>(0.01)|0.31***<br>(0.01)|||
|Diference|(_o_ - _d_) in ICRG|||||||0.24*** <br>(0.01)|0.26***<br>(0.01)|
|Constant||4.72*** <br>(0.03)|–2.94*** <br>(0.37)|4.73*** <br>(0.03)|–2.90*** <br>(0.38)|4.87*** <br>(0.03)|–2.97*** <br>(0.38)|4.84*** <br>(0.03)|–3.12***<br>(0.43)|
|Gravity co<br>Year FE|ntrols|No<br>Yes|Yes<br>Yes|No<br>Yes|Yes<br>Yes|No<br>Yes|Yes<br>Yes|No<br>Yes|Yes<br>Yes|
|Adj. R-Sq<br>|uare|0.08<br>|0.53<br>|0.08<br>|0.52<br>|0.09<br>|0.52<br>|0.10<br>|0.51<br>|
|N||6890|6053|6890|6053|6594|6053|5248|4813|

Robust standard errors clustered by county in parenthesis. ***, **, and * indicate statistical significance at the 1 _%_ , 5 _%_ , and 10 _%_ levels, respectively.

Table A3: Gravity controls interacted with corruption

|_Dependent Variable:_||Migration|Flows||
|---|---|---|---|---|
||WGI CC <br>(1)|WGI GE<br>(2)|CPI<br>(3)|ICRG<br>(4)|
|Diference (_o_ - _d_) in WGI CC<br>|1.88***<br>(0.17)||||
|Diference (_o_ - _d_) in WGI GE||2.81***<br>(0.26)|||
|Diference (_o_ - _d_) in CPI|||1.91***<br>(0.17)||
|Diference (_o_ - _d_) in ICRG||||1.40***<br>(0.16)<br>|
|Constant|–4.36*** <br>(0.36)|–4.05*** <br>(0.36)|–4.22*** <br>(0.36)|–4.43***<br>(0.42)|
|Gravity controls<br>|Yes<br>|Yes<br>|Yes<br>|Yes<br>|
|Gravity controls X Corruption<br>|Yes<br>|Yes<br>|Yes<br>|Yes<br>|
|Year FE|Yes|Yes|Yes|Yes|
|Adj. R-Square<br>N|0.57<br>6053|0.57<br>6053|0.56<br>6053|0.55<br>4813|

Robust standard errors clustered by county in parenthesis. ***, **, and * indicate statistical significance at the 1 _%_ , 5 _%_ , and 10 _%_ levels, respectively.

21
short run at the expense of regional growth rates in the long run, due to reduced educational attainment. Policy makers need to consider this negative externality when making rural development policies.

**Table 10: Survey of selected papers on the developing impact of rural roads in other regions**

|**Author**|**Level of**<br>**Analysis**|**Country/**<br>**Region**|**Indicator of**<br>**Development**|**Main Findings**|
|---|---|---|---|---|
|Emran and Hou<br>(2013)*|Household|China|Consumption|Reducing distance to domestic market, and to a lesser extent international<br>market, increases per capita consumption reducing rural poverty.|
|Khandker et al<br>(2009)*|Household|Bangladesh|Consumption/<br>Agriculture|Road improvement increases household per capita annual consumption,<br>and significantly boosts aggregate crop output, crop price indices and<br>education.|
|Jacoby (1999)+|Household|Nepal|Income<br>Inequality|Providing extensive road access to markets confers higher incomes, but not<br>enough to materially improve inequality.|
|Asher &<br>Novosad (2020)*|Village|India|Structural<br>Transformation|New feeder roads facilitate movement of workers out of agriculture, but<br>without any major changes in agricultural outcomes, income, or assets.|
|Blankespoor et<br>al (2017)|Localities|Mexico|Jobs,<br>Specialization|A 10% increase in market access results in a 2.9-6.5% increase in<br>employment, and a 13% increase in specialization, particularly for<br>commerce and services.|
|Martincus et al<br>(2017) *|Firms|Peru|Exports,<br>Employment|A 22% reduction in distance to the nearest port, led to 3.8% faster growth<br>in exports, with associated expansion of employment.|
|Li et al (2019)|Hukou<br>(district)|China|Education|Rural highway access reduces the enrollment rate of senior high (but not<br>junior high or elementary) schools due to improved access to jobs.|

Source: Compiled by the authors.

Note: Findings column is based on the main finding of the paper. An asterisk identifies peer-reviewed papers. Plus identifies papers following the instrumental variable approach.

# **5.2 National Highways**

Like rural roads, the expansion of quality trunk roads supports economic growth through various development indicators from output growth to more employment opportunities in remote areas. However, recent research (e.g., Ali et al, 2015; Damania and Wheeler, 2015) also points out that new road constructions also leads to significant economic costs, unless measures are taken to enhance security in conflict-affected zones and overcome negative environmental externalities due to deforestation.

Numerous papers explore the economic impacts of the construction of two of the biggest transportation investment programs in the world, namely the Chinese National Expressway Network and the Indian Golden Quadrilateral (GQ) Project. The former is designed to connect all Chinese cities with a population of more than 200,000 (World Bank, 2007), the latter aims to connect the largest metropolitan areas across India: Delhi (in the north), Calcutta (in the east), Chennai (in the south), and Mumbai (in the west). GQ spans 5,846 km, reaching 95 percent 32