rafmacalaba/datause-encoder-data huggingface dataset:
<u>Political Economy of American Trade Policy, Chicago, University of Chicago</u> Press.

- Finger, J. Michael, Merlinda D. Ingco and Ulrich Reincke. 1996. The Uruguay <u>Round: Statistics on Tariff Concessions Given and Received, Washington,</u> DC, World Bank.

- Gallaway, M., B. Blonigen and J. Flynn. 1999. ‘Welfare cost of the US antidumping and countervailing duty law,’ Journal of International <u>Economics,</u> vol. 49, no. 2, pp.  211-44.

-

- G-33, African Group and ACPs. 2008. Statement of G <u>33, African Group, ACP and SVEs on Special Products and Special Safeguards Mechanism, Geneva,</u> July 27

- GATT. 1994. Analytical Index: Guide to GATT Law and Practice, GATT, Geneva.

-

- GATT. 1990. The International Trade Environment, GATT <u>Report by the</u> -

- <u>Director General 1989 1990, Geneva, Switzerland.</u>

- GATT. 1958. Antidumping  and Countervailing Duties, Geneva, GATT.

- Hallaert, Jean-Jacques. 2005. Special Agricultural Safeguards: Virtual Benefits –

- <u>and Real Costs Lessons for the Doha Round, IMF Working Paper</u> WP/05/131.

- Hathaway, Dale E. 2001. A Special Agricultural Safeguard (SAS): buttressing the <u>market access reforms of developing countries, Paper prepared by the</u> FAO Commodities and Trade Division for the FAO Round Table on Selected Agricultural Trade Policy Issues, Geneva, 21 March 2001. Accessed September 22, 2008 at

http://www.fao.org/DOCREP/005/Y3733E/y3733e05.htm#fn35

- Hudec, Robert E. 1987. Developing Countries in the GATT Legal System, London, Gower for the Trade Policy Research Center

- Hull, Cordell. 1948. The Memoirs of Cordell Hull, 2 volumes, New York: Macmillan International Center for Trade and Sustainable Development (ITCSD). 2008.

- ‘Members Give Mixed Reactions to Lamy Compromise, Take “A Good Step Forward” On Services,’ BRIDGES Daily Update, 27 July 2008.

- Jales, Mario. 2005. Tariff Reduction, Special Products and Special Safeguards: An -

- <u>Analysis of the Agricultural Tariff Structures of G 33 Countries,</u> International Center for Trade and Sustainable Development, Geneva, July

- Little, Ian M. D. 1982. Economic Development: Theory, Policy and International <u>Relations,</u> New York, Basic Books.

- Laborde, David, Will Martin and Dominique van der Mensbrugghe. 2009. ‘Implications of the 2008 Doha Draft Agricultural and NAMA Market Access Modalities for Developing Countries,’ paper presented at the Eleventh Annual Conference on Global Economic Analysis, Helsinki, 12-14 June. www.gtap.org.

41
> - 13 -

The adoption of border prices would brlng galns and losses at the farm level even though the Impact on mean net output Is small. Nlnety percent of producers In 1987 would have had net farm output at border prices (at two rubles to the dollar) within a range of 83 percent to 116 percent of received net farm output (actual prices). The ninety percent Interval for 1986 Is bounded by .81 and 1.19. Thus the Introductlon of prices based on border prices converted at two rubles to the dollar would brlng short run gains and osses between 10 percent and 20 percent of farm Income for ten percent of farms. Long run changes would depend on the supply response to the new relative price structure.

The finding that net farm output In Lithuanla would change llttle If border prices (at two rubles to the dollar) were substituted for current prices Is new and bnportant. Its Importance Is enhanced by the absence of any rlgorously Justifiable estImates of an equIlibrlum exchange rate for the ruble.

Wlthout knowledge of an equlilbrIum exchange rate, and In the absence of a general price liberalIzation, those deslgning administrative adjustments of agricultural producer prices must use their Judgement about what exchange rates are feasible In a partial, sector specific price revision, considering the Impact on farm Incomes and consumer budgets. The LIthuanlan data Indlcate that an Implied exchange rate of fewer than two rubles to the dollar would bring a hlghly undesirable supply shock associated wlth the new price structure. In some parts of the Soviet Union where producer costs and prices are higher than In Lithuanla, a supply shock may be a necessary part of the adjustment process to remove marginal producers. There Is little Indication of a need for exit of many marginal producers In Lithuania, If they can operate with the current relatively low producer prices.

Although 1987 levels of farm Income were roughly consistent with an exchange rate of two rubles to the dollar, and producers realized Implicit rents under the current system, It would be difficult to Introduce land payments wlthout raising the
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<!-- Start of picture text --> Phase Classification (IPC) assessment of end of 2022 (IPC, 2022)<br>are severely impaired. The food security challenges faced by Yemen are significant, and the number of<br>intricate connections among conflict, poverty, extreme weather, climate, and food price shocks<br>physical and mental health consequences. Prior to the 2015 escalation of conflict, Yemen already had<br>one of the world’s highest malnutrition levels. The situation has been aggravated by escalating conflict<br>of life, severe food crises inflict lasting harm on the children of affected families, resulting in<br>enormous humanitarian aid. According to World Bank data on aid and official development assistance,<br>Yemen received 8 billion dollars in official development assistance alone in 2018. At the $1.90 dollar<br>poverty line, this was sufficient to pay for almost 90% of the annual expenses of the population FAO<br><!-- End of picture text -->
receive land from households concentrated in other activities (e.g., Benjamin and Brandt, 2002). Thus, both observed and unobserved characteristics of individuals and households that are associated with loss of land may simply reflect household decisions to shift out of agriculture and the ability of younger and more educated residents to engage in non‐agricultural activities.

Considering both the scale and rapid increase in rural‐to‐urban migration in China over this period, it may at first seem counterintuitive to spend much time dwelling on barriers to migration. Residents of rural China, however, have faced important institutional barriers to geographic mobility throughout the reform period, and rising rural‐urban income gaps offer prima facie evidence that migration flows have not proceeded rapidly enough to offset differences in productivity growth between rural and urban areas (Park, 2008). Upon examination of micro data from rural China, it becomes apparent that there is tremendous heterogeneity across villages in levels of out‐migration over the reform period, and that this period was also characterized by sharp increases in inequality within rural areas (Benjamin et al, 2005; Ravallion and Chen, 2007). Considerable effort has gone into studying the effects of the household registration system (or _Hukou_ system) on migration, with research emphasizing such topics as the the gap in rural‐urban wages (e.g., Liu, 2005) and the presence of under‐sized cities with unexploited economies of scale (Au and Henderson, 2006). At the same time, there is a relative paucity of work describing how variation in land tenure security across rural China may have influenced migration decisions, with likely implications for differences in incomes and consumption across villages.

Over the period under study, there was considerable variation in _de facto_ land tenure security across China’s villages. Under China’s constitution, rural land is the property of administrative villages, or collectives, but exclusive use rights are contracted out to individual households. As in many other developing countries, China has laws with provisions to formally protect individualistic land use rights, but enforcement mechanisms do not necessarily exist or function as intended (e.g, Benjamin and Brandt, 2002; Brandt et al, 2004; Dieninger and Jin, 2009; Jacoby et al, 2002).

_Land Tenure Insecurity and Migration, Page 4_
# **REFERENCES**

- ABDULAI, A. & CROLEREES, A. 2001. Determinants of income diversification amongst rural households in Southern Mali. _Food policy,_ 26 **,** 437-452.

- ACKAH, C. 2013. Nonfarm employment and incomes in rural Ghana. _Journal of International Development,_ 25 **,** 325-339.

- ADJOGNON, S. G., LIVERPOOL-TASIE, L. S. O. & REARDON, T. A. 2016. Agricultural input credit in Sub-Saharan Africa: Telling myth from facts. _Food Policy_ .

- BARDHAN, P. & UDRY, C. 1999. _Development microeconomics_ , Oxford University Press.

- BARRETT, C. B., BEZUNEH, M. & ABOUD, A. 2001a. Income diversification, poverty traps and policy shocks in Côte d’Ivoire and Kenya. _Food Policy,_ 26 **,** 367-384.

- BARRETT, C. B., REARDON, T. & WEBB, P. 2001b. Nonfarm income diversification and household livelihood strategies in rural Africa: concepts, dynamics, and policy implications. _Food policy,_ 26 **,** 315-331.

- BASER, O. 2009. Too much ado about instrumental variable approach: is the cure worse than the disease? _Value in Health,_ 12 **,** 1201-1209.

- BEZU, S. & BARRETT, C. 2012. Employment dynamics in the rural nonfarm sector in Ethiopia: Do the poor have time on their side? _Journal of Development Studies,_ 48 **,** 12231240.

- BEZU, S., BARRETT, C. B. & HOLDEN, S. T. 2012. Does the nonfarm economy offer pathways for upward mobility? Evidence from a panel data study in Ethiopia. _World Development,_ 40 **,** 1634-1646.

- CAMERON, A. C. & TRIVEDI, P. K. 2005. _Microeconometrics: methods and applications_ , Cambridge university press.

- CAMERON, A. C. & TRIVEDI, P. K. 2010. _Microeconometrics using stata_ , Stata Press College Station, TX.

- CAPPELLARI, L. & JENKINS, S. P. 2003. Multivariate probit regression using simulated maximum likelihood. _The Stata Journal,_ 3 **,** 278-294.

- CHAMBERLAIN, G. 1982. Panel data. National Bureau of Economic Research Cambridge, Mass., USA.

- DAVIS, B., DI GIUSEPPE, S. & ZEZZA, A. 2014. Income diversification patterns in rural subSaharan Africa: reassessing the evidence. _World Bank Policy Research Working Paper_ .

22
Second, the results in Table 10 provide evidence that narrow incumbent victories are associated with a larger increase in the number of post-election casualties in areas with active insurgency presence.<sup>19</sup> Specifically, the results in column (2) suggest that narrow incumbent victories in areas with no active insurgency presence are associated with a statistically insignificant 0.21 increase in the number of post-election casualties. By contrast, the effect in areas where insurgents are active suggests an additional increase of 0.53, significant at the 5 percent level. Reassuringly, there is no relationship between narrow incumbent victories and post-election violence in areas with or without insurgency presence. The data also allows the analysis to distinguish between violent incidents involving the NPA or other lawless elements. The results in Table 7 indicate that the increase in violence after an incumbent’s narrow victory involves both insurgents belonging to the NPA as well as other lawless elements. There is no such relationship in the pre-election period. The results of estimating the relationship between narrow incumbent victories and violence based on the group who initiated the violent incidents are reported in Table 8. The analysis distinguishes between incidents initiated by AFP or rebel groups. The results in columns (1)-(4) indicate that both the AFP and rebel groups initiate incidents of violence after a narrow incumbent victory. However, as shown in Table 9, the AFP is the group that suffers most of the casualties after a narrow incumbent win.

> 19Based on an intelligence assessment conducted in 2001, the AFP assigned villages into three categories of rebel activity: threatened, influenced and infiltrated. Insurgent presence is defined as having at least one village in the municipality in any of the three categories.

30
38 area of residence negatively affects the probability of owning one or two vehicles.

The class/vintage choice for one and, separately, two vehicle households is significantly affected by purchase price and vehicle age. Operating cost is marginally significant. From the results, a lower income (<$12,000/year) household is willing to pay up to $844 in the purchase price for a one cent per mile reduction in operating cost. This figure is far less than the present discounted savings in operating costs.

VMTs for one and, separately, two-vehicle households are estimated in the log form using instrumental variables. Instruments are applied to a variable for the operating cost of the vehicle it chooses (an endogenous variable). These instruments have much policy significance, and include gas price, number of transit trips in area, and distance to work, among others. Operating cost is the only significant variable for one-vehicle households, with a coefficient of -0.2795, implying that a one-cent increase in operating cost reduces VMTs by 1300 miles per year.22 For two-vehicle households, operating cost is highly insignificant. Income and transit trips are the only significant variables (besides whether the vehicle is the newer of the household's vehicles).

Finally, the division of VMTs in different categories of trips is made with a multinomial logit model. Within a city, gas prices significantly affect non-work, but not work trips. The proportion of household members who work affects work trips. Household size is marginally significant. This model and its data base are now being up-dated by the USEPA (called the Consumer Automotive Response (CAR) Model) for use in forecasting C02 22. If operating costs are $.20/mile and VMTs are 10,000, this implies an elasticity of over 2. This seems very high.
# **1.** **_INTRODUCTION_**

The year 2007 marked a turning point in the long term trend in crime and violence in Mexico. After more than 20 years of sustained reduction, Mexico experienced a dramatic increase of 300 percent in homicide rates between 2007 and 2011. A growing literature concludes that several compounding factors contributed to this sudden escalation of violence and crime: the success of Plan Colombia, the expiration of the U.S. Federal Assault Weapons Ban, the escalation of conflicts among Mexican cartels, and President Calderon’s decision to send military troops to fight them. The wave of violence was further exacerbated by government policies that eliminated the leaders of criminal organizations, leading to disputes among a larger number of cartels struggling for control of a fragmented drug business.

The turning point of violence translated into a higher demand for inputs from Mexican criminal organizations. According to Guerrero (2011), the Federal Government’s so-called war on drugs (2007-2012) pushed cartels towards greater professionalization, including the outsourcing of specialized criminal services to street gangs (drug transportation and sale, kidnapping, extortion, and murder, for example). Cartels and gangs established a relationship of mutual benefit (Guerrero 2010b). This alliance became long lasting in part due to the gangs’ blunt and effective use of violence, with children and teenagers playing a key role. “...[I]n some gangs, training in violence starts at 12 years old. When these children reach 18 years old, they are experts in the use of violence” (Guerrero 2010a).

The change of the organizational structure of criminal activities put young Mexicans at risk, particular those with low education or early school drop outs. It is now a well-documented fact that crime is far more common among men than women and it tends to rise during their late teens, peak at around the early twenties and then decline rapidly (Hansen 2003, McCall 2013, and Chioda 2015, among others). There is also growing evidence that high school drop outs have a higher probability of engaging in criminal activities (Anderson 2014 and Chioda, de Melo, and Soares 2012). In Mexico, information from administrative records on all alleged criminals in 2007 shows that 90 percent of those undergoing the judicial process were men, 2
|omen<br>(6)|0.00111**<br>(0.000508)|0.00217***<br>(0.000485)|0.330***|(0.0318)|Yes|0.0424<br>0.220|1034|: dep var = 1|ng one out.|s the p-value|||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Net w<br>(5)|0.00103**<br>(0.000513)|0.00212***<br>(0.000489)|0.331***|(0.0320)|No|0.0355<br>0.208|1034|RO. Columns 3-4|t application flli|ken. Test display|errors||
|tling<br>(4)|-0.000782<br>(0.00123)|0.00364***<br>(0.00107)|0.735***|(0.0654)|Yes|0.0000223<br>0.126|261|lly paid for a C|p and flling ou|other action ta|obust standard||
|Co-ti<br>(3)|-0.00127<br>(0.00114)|0.00341***<br>(0.00102)|0.750***|(0.0607)|No|0.00000398<br>0.105|261|household has fu|ional on taking u|ation, zero if any|ents are equal. R||
|e-up<br>(2)|0.00278***<br>(0.000611)|0.00320***<br>(0.000561)|0.461***|(0.0367)|Yes|0.482<br>0.283|1034|variable = 1 if|lication, condit|on CRO applic|voucher coefci||
|Tak<br>(1)|General voucher value (tsh ’000)<br>0.00257***<br>(0.000614)|Conditional voucher value (tsh ’000)<br>0.00309***<br>(0.000572)|Constant<br>0.476***|(0.0370)|Baseline controls<br>No|Test: _βG_ =_βC_<br>0.387<br>_R_2<br>0.256|Obs<br>1034|**Notes:** Linear probability model. Columns 1-2: Dependent|if household has included a woman as co-owner on CRO app|Columns 5-6: dep var = 1 if household has included woman|from a linear test of the hypothesis that general conditional|_∗p <_0_._10_,∗∗p <_0_._05_,∗∗∗p <_0_._01|

22
|Telecommunications Project(02)|Veronique Bishop|
|---|---|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Telecommunications Project(02)|Veronique Bishop|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Upland Agriculture Development Project|Supee Teravaninthorn|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Forest Management and Conservation Project|William B. Magrath|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Provincial Grid Integration Project|Enrique O. Crousillat|
|Structural Adjustment Credit Project||
|Structural Adjustment Credit Project||
|Structural Adjustment Credit Project||
|Structural Adjustment Credit Project||
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
|Health System Reform and Malaria Control Project|Hope C. Phillips Volker|
Policy Research Working Paper 5522

# **Abstract**

Using panel data from Mozambique collected in 2007 and 2008, the authors explore the impact of the food crisis on the welfare of households living with HIV/ AIDS. The analysis finds that there has been a real deterioration of welfare in terms of income, food consumption, and nutritional status in Mozambique between 2007 and 2008, among both HIV and comparison households. However, HIV households have not suffered more from the crisis than others. Results on the evolution of labor force participation suggest that initiation of treatment and better services in health facilities have counter-balanced the effect of the crisis by improving the health of patients and their labor force participation. In addition, the authors look at the effect of the change in welfare on the frequency of visits to a health facility of patients and on their treatment outcomes. Both variables can proxy for adherence to treatment. This is a particularly crucial issue as it affects both the health of the patient and public health, because sub-optimal adherence leads to the development of resistant forms of the virus. The paper finds no effect of the change in welfare on the frequency of visits, but does find that people who experienced a negative income shock also experienced a reduction or a slower progression in treatment outcomes.

This paper is a product of the Human Development and Public Services Team, Development Research Group. 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://econ.worldbank.org. The authors may be contacted at ddewalque@worldbank.org, harounan.kazianga@okstate.edu, mover@cgdev.org and julia.vaillant@gmail.com.

_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