rafmacalaba/datause-encoder-data huggingface dataset:
# **I. Introduction**

During the past decade researchers at the World Bank and a number of partner institutions have been studying approaches to develop detailed “poverty maps” in a large number of developing countries. These maps provide estimates of (consumption or income) poverty and inequality at the local level – such as the sub-district and even community level. In general this information is not available because sample surveys do not normally permit sufficiently fine disaggregation. Yet, with ongoing efforts to apply detailed spatial targeting of public interventions, or to realize the gains from decentralization and from a greater focus on community-centered development, there is a pressing need for information on distributional outcomes at the local level. In the approach introduced in Hentschel, Lanjouw, Lanjouw and Poggi (2000) and refined further in Elbers, Lanjouw and Lanjouw (2002, 2003), household survey data are combined with unit record data from the population census in order to overcome these data constraints. The resulting welfare estimates can be used to better understand the spatial distribution of economic wellbeing and to investigate the relationship between poverty and other geographic factors.<sup>1</sup> These poverty maps aim to provide not only estimates of poverty or inequality levels at the local level, but to also provide a sense of the precision of these estimates. Although their potential value is wellrecognized, opportunities to formally check the reliability of the local-level poverty estimates and their associated confidence intervals are rare. Such validation exercises are needed if these smallarea estimation methods are to enter into regular use and their outputs are to inform policymaking.

In a recent study, Tarozzi and Deaton (2007) suggest that the methodology developed by Elbers, Lanjouw and Lanjouw (2002, 2003) - henceforth ELL (2003) – is likely to yield an overly

> 1 Poverty maps have been produced or are underway in some 40-50 developing countries.  Alongside their descriptive function in conveying information on the spatial distribution of poverty, the databases underpinning these maps have been used in a variety of policy-related studies (see for example, Demombynes and Ozler, 2005, Fujii and Roland Holst, 2007, Elbers et al, 2007, Araujo et al, forthcoming).  In addition, the approach developed in ELL, 2003, has also prompted further methodological research aimed at, for example, estimating child nutritional outcomes at the local level (Fujii, 2005) or imputing welfare indicators across household surveys (Christiaensen and Stifel 2007, Kijima and Lanjouw, 2003)

2
# **5. Data**

This study uses quarterly data from the National Employment Survey _“Encuesta Nacional de Ocupación y Empleo”_ of Mexico, a rotating panel of households. There are two periods of implementation (ENE: 2000-2004) and (ENOE: 2005-2009). It is nationally representative but, strictly speaking, the ENE survey had an adequate frame only for the urban population. The data includes a rotating panel at the individual and household level (2000-2009)<sup>6</sup> .

The data cover almost 10 million individuals from 2000 (Q2) to 2009 (Q2) between 15 and 65 years old<sup>7</sup> in 291 municipalities across the country<sup>8</sup> . We observe whether a specific individual changes _SS_ status (provided by formal employment) over consecutive periods. We also observe whether the individual is covered by _SS_ through the spouse or directly through his or her job. At the household level we have an average of 100,000 households per period. Figure 1a shows the quarterly trend of the share of individuals with _SS_ and households covered by _SS_ . Formality exhibits an upward trend more so after the first quarter of 2005. Figure 1b shows the trends of the shares of population by their labor market status. There is a drop in the share of wage employees without SS and other informal employment at around the fourth quarter of 2004 but for the most part the shares are stable.

<!-- Start of picture text --> Figure 1a. Share of Households and Individuals with Social Security Figure 1.b. Shares of Population by Labor Market Status<br>2000q1 2001q3 2003q1 2004q3 2006q1 2007q3 2009q1<br>date<br>2000q1 2001q1 2002q1 2003q1 2004q1date2005q1 2006q1 2007q1 2008q1 2009q1 wage-employed with ss self-employed<br>wage-employed without ss not in labor force<br>share individual with ss share household ss covered other informal employment<br>source: Labor Surveys source: Labor Surveys<br>.4<br>.3<br>.2<br>.1<br>0<br>.45<br>.4<br>.35<br>.3<br>.25<br><!-- End of picture text -->

> 6 There are three fifths of individuals at the end of 2004 that rollover to ENOE in 2005. However, in view of some methodological changes implemented to the ENOE relative to the ENE which could affect observations overlapping the two panels, we chose to discontinue rollover of individuals into 2005. In our estimates, differences in methodology across the two datasets are accounted for with either a survey dummy  or with household fixed effects. 7 About 370,000 individuals per quarter.

> 8 Mexico has 2,456 municipalities in 2009 and the data covers 1,272, however we eliminated municipalities that: 1) do not have at least 50 observations once; 2) do not have at least 30 observations which appear at least 4 consecutive quarters.

13
Welch, J. G. (2014). HOPE for community college students: The impact of merit aid on persistence, graduation, and earnings. _Economics of Education Review_ , _43_ , 1–20.

- Wiederspan, M. (2016). Denying loan access: The student‐level consequences when community colleges opt out of the Stafford loan program. _Economics of Education Review_ , _51_ , 79–96.

- Williams, G., & Gordon, A. (1981). Perceived earnings functions and ex ante rates of return to post compulsory education in England. _Higher Education_ , _10_ (2), 199–227.

- Wolter, S. C. (2000). Wage Expectations: A Comparison of Swiss and US Students. _Kyklos_ , _53_ (1), 51–69.

42
- Tarazi, Michael, and Paul Breloff. 2010. “Nonbank E-Money Issuers: Regulatory Approaches to Protecting Customer Funds.” CGAP Focus Note No. 56629, Consultative Group to Assist the Poor, Washington, DC.

- United Nations Development Programme (UNDP). 2022. _Human Development Report 2021/2022. Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World._ New York, NY.

- World Bank. 2019. _Global Financial Development Report 2019/2020: Bank Regulation and Supervision a Decade after the Global Financial Crisis._ Washington, DC: World Bank. doi:10.1596/978-1-4648-1447-1.

- World Bank. 2020. The Human Capital Index 2020 Update: Human Capital in the Time of COVID-19. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/34432 License: CC BY 3.0 IGO.

World Bank. 2020a. _Global Economic Prospects_ , January 2020. Washington, DC: World Bank.

World Bank. 2020b. _Global Economic Prospects_ , June 2020. Washington, DC: World Bank.

- World Bank. 2021. _World Development Report 2021: Data for Better Lives._ Washington DC: World Bank. doi:10.1596/978-1-4648-1600-0.

- World Bank. 2022. _Poverty and Shared Prosperity 2022: Correcting Course_ . Washington, DC: World Bank. <u>http://hdl.handle.net/10986/37739.</u>

- Wyman, Oliver. 2017. _Accelerating Financial Inclusion in South-Asia with Digital Finance_ . Asian Development Bank. <u>https://dx.doi.org/10.22617/RPT178622-2</u>

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# **<<B>>** HFA (Primary Data)

Observations of CPIs were done for clients seeking ANC for the first visits (under 24 weeks) and last visits (36 weeks or more); PNC within 48 hours, two weeks, and four to six weeks; STI treatment; and family planning services. Although family planning was not initially one of the services subsidized by the maternal health voucher program, a follow-up program to subsidize the services had already been initiated through additional funding from the United States Agency for International Development (USAID), hence the rationale for conducting CPIs for family planning. Trained nurses conducted the CPIs. They observed both the process (how clients were treated and whether they actively participated) and the content (what clients were told, technical competence of the SP, accuracy of information, and provision of essential information) during consultation. In both contracted and comparison facilities, six clients were selected for each ANC and PNC component, as well as family planning services in each facility. At facilities with more than six clients at the time the research assistants visited, six clients were selected at random. Written informed consent was obtained from the clients before conducting the CPIs. Table A2 in the appendix presents the distribution of CPIs that were conducted using various background characteristics for each of the services.

Interviews with SPs targeted those working in the maternal and child health and family planning units in the facilities included in the 2010 HFA. All SPs in these units were eligible for the interviews. Information was obtained about their knowledge, attitudes, and practices regarding reproductive health issues, including ANC, delivery care, PNC, STIs and HIV, family planning, gender-based violence, and vouchers. Either the nurses or the social scientists conducted the interviews after obtaining written informed consent from the SPs. Table A3 presents the distribution of SPs who were interviewed based on various background characteristics. Similar to the household surveys, the Institutional Review Boards of the Population Council and Mbarara University granted ethical clearance for the HFA.

**<<B>>** Secondary Data Sources

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_Brazilian spatial labor dynamics Page 33_

# Salary Growth

<!-- Start of picture text --> Salary Growth - 91/00<br>-1.524 - -0.5<br>-0.5 - 0<br>0 - 0.3<br>0.3 - 0.85<br>N<br>W E<br>1000 0 1000 2000 Miles<br>S<br><!-- End of picture text -->

**Map 2**

Salary. Brazil. 2000.

<!-- Start of picture text --> Salário - 00<br>325.614 - 2500<br>2500 - 5000<br>5000 - 7500<br>7500 - 16701.68<br>N<br>W E<br>0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Kilometers S<br><!-- End of picture text --> <!-- Start of picture text --> Map 3<br><!-- End of picture text -->
# **IV. Economic Growth and Political Violence: The Evidence**

The model in section II suggests that the onset of political violence reduces economic growth and increases its volatility.<sup>13</sup> However, the received literature on civil war and other political violence also suggests that economic factors, including economic growth and income per capita, determines the opportunity costs of peace as well as the ability of the state to quell a potential challenge to its authority. Moreover, the some of the recent empirical literature suggests that these economic factors are robust determinants of the hazard of violent political conflicts.<sup>14</sup> Furthermore, economic outcomes (growth and income per capita) associated with political violence are themselves endogenous to the economic and political institutions that govern the organization of the political processes and economic activities in a society. In turn, the prevailing economic and political institutions are influenced and shaped by deeper societal and geography characteristics.<sup>15</sup> Most empirical evidence on the relationship between institutions and ethnic fractionalization appears to support the view that social fractionalization, especially ethnic fractionalization, constitutes a challenge for the emergence of development-oriented institutions and is, therefore, associated with a bad policy environment. For example, Easterly and Levine (1997) establish that ethnic diversity leads to bad policy, which, in turn, decelerates growth, both effects being quite powerful. Indeed, they suggest that much of Africa’s slow growth is attributable to its ethnic diversity. Ethnic diversity has also been shown to contribute to government dysfunction in several areas of economic policies, both in developed and in developing countries alike. For example, local or central governments in ethnically diverse societies tend to under-spend on public goods and education (Alesina, Baqir and Easterly, 1999; Goldin and Katz, 1999); produce low quality of services (Mauro, 1995; La Porta, 1999); generate greater political instability (Mauro, 1995; Annett, 1999); or misuse foreign aid and divert it into corruption (Svensson, 2000).<sup>16</sup> Africa specific literature, based on survey data, also finds evidence of dysfunction in government and civil society organizations. For example, Collier and Garg (1999) find that employment in the public

> 13 The analysis of the impact of political violence on growth volatility is beyond the scope of this paper. 14 See, for example, Sambanis (2004) for a comprehensive review of the empirical evidence on the determinants of civil war; and Bodea and Elbadawi (2007) on the determinants of riots, coups and civil wars in a multinomial model of political violence.

> 15 There is recently an active debate on the “deep” determinants of growth and income disparities across nations and sub-national regions (for a review of the debates, see, for example, Easterly and Levine, 2003, Rodrik, Subramanian and Trebbi, 2004, and Elbadawi, 2005).

> 16 See Easterly (2001a, b) and Collier (2000) for more detailed review of this literature.

14
30 The financial gas market is gradually reaching maturity, especially in standardized contracts as indicated by the small share of futures contracts resulting in physical delivery (table 4). On average, only 0.26 percent of natural gas futures contracts traded on NYMEX were held until expiration in 1995, compared with 0.14 percent of crude oil futures contracts (the most mature contract traded on NYMEX), 0.18 percent of heating oil futures contracts, and 3.4 percent of propane futures contracts. The low level of physical delivery indicates that market participants use futures contracts as an instrument - - for price risk management their primary purpose not for physical gas delivery.

**Table 4 Delivery Structure of Natural Gas Contracts at NYMEX, 1993-96** (millions of British thermal units)

|Year|Deliveries of<br>futures|Futures<br>trading volume|Deliveries of EFPs|Deliveries as a<br>percentage of<br>trading volume|
|---|---|---|---|---|
|1993|10,417|3,775,517|79,725|0.28|
|1994|15,923|6,223,401|147,039|0.26|
|1995|20,025|7,621,742|209,323|0.26|
|1996|13,223|4,556,290|142,371|0.29|

_Source:_ NYMEX.

Most of the final deliveries of financial gas contracts at NYMEX took place under EFPs, whose delivery rate is about 10 times that for futures. While futures contracts are used for hedging and speculation at only three locations (the Henry Hub, West Texas, and Alberta), EFPs can be used for delivery at any location. Thus EFPs can hedge the risk of changing price differentials between a standard delivery location and any location in the nationwide pipeline system and are naturally used more often than standard futures contracts.

The natural gas market has become more efficient with the increasing use of futures contracts. De Vany and Walls (1995) analyzed cointegration between spot and futures prices between June 1990 and June 1994 and found evidence that prices in the futures market accurately reflected the future spot prices of gas at the Henry Hub and seven major spot markets. They also found that the price differentials between locations reflected the costs of transportation. They concluded that the futures prices of a monthahead contract revealed the closing futures price, and that spot prices in the Henry Hub are an unbiased predictor of the future spot price.

# **Transportation Market**

A natural gas transportation market is a marketplace where pipeline capacity and transportation services are traded. The interstate pipeline transportation market is the most competitive transportation market in the United States because of the unbundling of
availability of business services results in total factor productivity gains to the manufacturing sector and the economy of the host country more broadly.<sup>5</sup> We extend to FDI the logic of Arkolakis _et al_ . (2012) regarding the importance of holding the trade response constant across model structures for a fair comparison of the welfare effects of market structures. That is, we hold the FDI response constant in the Melitz, Krugman and Armington (to the extent possible) market structures. Our estimated welfare gains from FDI liberalization in our Krugman and Melitz models are about double the estimated gains in the Armington model.

An additional innovation is that we break the all varieties are consumed everywhere property of the Krugman (1980) model. This responds to the stylized fact that small economies, especially small developing economies, typically have fewer varieties available than large developed economies. This significantly impacts the results, as our small open economy then reaps a non-trivial Dixit-Stiglitz externality gain on additional varieties of goods or services, including services provided by FDI.

We apply these models to the impact of the Regional Comprehensive Economic Partnership (RCEP) on The Philippines. With the withdrawal of the United States from the Trans-Pacific Partnership (TPP), 16 countries in Asia and the Pacific (the ASEAN 10, China, Japan, India, the Republic of South Korea, Australia and New Zealand) have turned more earnestly to negotiations of RCEP.<sup>6</sup> Collectively, these countries account for almost half of the world’s population and almost thirty percent of the world’s GDP.

The guiding principles of RCEP<sup>7</sup> call on the member governments to progressively eliminate tariff and non-tariff barriers on substantially all trade in goods; to substantially eliminate restrictions or discriminatory measures with respect to trade in services among RCEP members; and to facilitate investment in the region. There are also discussions in RCEP meetings regarding trade facilitation, especially with respect to the improvement of customs procedures.

> 5 See Francois and Hoekman (2010) for a survey of the theory and more than a dozen empirical studies that support this finding.  In addition, in recent years, several studies that use firm level data support the finding that FDI and the wide availability of business services results in total factor productivity gains to the manufacturing sector and the economy broadly. These include Arnold _et al_ . (2011) for the Czech Republic, Fernandes and Paunov (2012) for Chile, Arnold _et al_ . (2016) for India, Shepotylo and Vakhitov (2015) for Ukraine and Duggan _et al_ . (2013) for Indonesia. Two of the important theoretical papers are Markusen (1989; 1995).

> 6 Between 2012 and March 2017, there were 17 negotiation rounds. For summaries of these rounds and Ministerial meetings, see:  http://dfat.gov.au/trade/agreements/rcep/Pages/regional-comprehensive-economic-partnership.aspx

> 7 http://dfat.gov.au/trade/agreements/rcep/Documents/guiding-principles-rcep.pdf

3
**DIEASIIEG** ME **PogSDIZBZLXTIE** OF JO=U-FUE SUDS!TUT!ION

# **Table** of Contents

|CMMPTreIs|XXrRODUCrIOK .....<br>.<br>....................<br>.90*0<br>.................. 01|
|---|---|
|**ChAPTER2S**|**UVIDIUCUonZNTErVumU.**S**DTITUTION**........................<br>. 6|
||FuelUse in**the**<br>**O.E.C.D**<br>.........<br>**.**<br>........<br>6|
||Changes in Fuel Use in the O.E.C.D .................<br>8|
||Total Industry Disaggregation by Countries within<br>th O.E.C.D<br>.................<br>11|
||Fuel 8hares in Various Industrles in O.E.C.D ........ 15|
||Fuel Use Outside the O.R.C.D ......................<br>Is|
||Fuel Use in Industry OuteLde the O.Z.C.D ............ 18|
||Fuel Use in Power GoneratLon Outside the O.E.C.D.o. 20|
|CNAPT3R 3:|NXDTOD8 FOR 3STXZRTIU<br>-E*UUSTZTUTA5ZLITY OF|
||EconometrLc Studies of Fuel Substitutability ........ 28|
||The Engineering Approach ............................ 40|
||Non Site Specific Choice of Power Generation<br>Technology ......99*oe...........**...**<br>o<br>.....................<br>42|
||Site Specific Choice of Power Generation<br>T,echnlologWyo<br>......<br>.***.....<br>.....<br>...................................................<br>*45|
||A Comparison of the Econometric and Engineering<br>Fuel Substitutabllltyo .... .....**.........**<br>o<br>..... ............<br>49|
|CRIMTCR4t|**UVIDECS**<br>**ONFMU**<br>**WITCEI**<br>Z LATSCICIS<br>..............<br>53|
||Elasticities in the Electrical Power Generation<br>Sector.****...**a<br>.... ,....<br>o .<br>.....<br>*53|
||Elasticities of Fuel Switching in Industry .......... 56|
||Problems of Using Estimates of Inter-Fuel<br>Fuel Substitutability .......................................<br>68|
|BIBLIOGuuRPY ..|*.**.........<br>..........<br>..........<br>.....<br>75|
**Table 7:** Reservation wage correlates

||Re|servation|Wage (Lo|g)|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Wage growth belief|-0.031<sup>_∗_</sup><br>(0.018)||||
|Discount factor||-0.417<sup>_∗∗_</sup><br>(0.169)|||
|Discount factor (Inc.)|||-0.004<br>(0.109)||
|Liquidity Constrained||||-0.103<sup>_∗_</sup><br>(0.055)|
|Observations|533|1362|619|552|
|R square|0.01|0.00|0.00|0.01|

Notes: Source: Endline survey. The dependent variable is the log of reservation wages reported at endline. _Wage growth belief_ measures the perceived percentage increase over a six months spell. _Discount factor_ measures how much people discount future payments, collected in the inperson edline. _Discount factor (Inc.)_ captures the incentivized measure of how much people discount future payments, collected in the SMS edline. _Liquidity constrained_ is a dummy measuring whether people are not able to raise funds for a risk free profitable investment. Robust standard errors are presented in parentheses.<sup>_∗_</sup> _p <_ 0 _._ 10,<sup>_∗∗_</sup> _p <_ 0 _._ 05,<sup>_∗∗∗_</sup> _p <_ 0 _._ 01

# **5.5 Other explanations**

In addition to underestimating wage growth, youths may also under-value coverage by social security programs, either because they are not aware of these programs and / or heavily discount these future benefits. In the endline survey we ask participants whether they know what constitutes a formal job: 31% of the control group did not known, suggesting that a lack of knowledge may be a partial explanation for low rates of formal work. The share is reduced to 17% in the treatment group, indicating that the wage incentive helps to raise awareness. We also ask how much of their salary participants would be willing to have deducted in order to be covered by social security programs. The average (median) response is 17% (14%) of their wage.<sup>33</sup> This is considerably lower than the legally mandated social security contributions, which stand at around 26% of formal wage rates (Levy, 2010).<sup>34</sup> However, it is unclear whether this means that job seekers underestimate the _marginal_ benefit

> 33In the treatment group the willingness to pay is 55 pesos (5.7%) higher. However this difference is not significant (p-value: 0.136).

34This gap can help explain why formal firms in Mexico often hire workers informally (de la Parra, 2017).

35