rafmacalaba/datause-encoder-data huggingface dataset:
We focus in particular on one question with important similarities to the advanced country literature noted above- the role of the informal labor market- both because of the topic’s intrinsic interest, and because it offers a case study through which to view the strengths and weaknesses of these tools. Though a notoriously elusive concept, we define the informal sector as comprising the mass of owners of and or workers in small firms who are uncovered by labor legislation.<sup>2</sup> At the risk of excessive stylization, one view with conceptual roots in Harris and Todaro (1970) equates the informal sector with underemployment or disguised unemployment- the disadvantaged sector of a market segmented by rigidities in the “formal” or covered sector of the economy.<sup>3</sup> However, another emerging view keys more off the mainstream self-employment literature in the style of Lucas (1978), Jovanovic (1982) and Evans and Leighton (1989), and argues that, as a first approximation, entry into the sector should be seen as a vocational choice in line with the worker’s comparative advantage, to work in a more entrepreneurial sector, albeit one with irregular relations with the state.<sup>4</sup> We show that nature of the aggregate Markov-based statistics as reduced forms capturing both comparative advantage considerations as well as barriers to mobility makes drawing inferences from the observed patterns difficult. We therefore explore additional identification strategies exploiting some of the predicted patterns of worker dynamics suggested by the competing hypotheses about informality.<sup>5</sup> The results suggest that a substantial part of the informal sector, particularly the self-employed, corresponds

> 2  A minority, generally no more than 25% of the informal salaried workers are found in firms of over 6 workers (see Perry et. al 2007) so this is primarily a micro firm phenomenon.

> 3   This is, in fact, an extreme stylization although its essential focus on the dualism of the labor market and the intrinsic inferiority of informality is common to many models. See Schneider and Enste (2000) for a more comprehensive review of existing views. A rich theoretical literature is emerging that poses more sophisticated mechanisms that relate informality to unemployment. See, for example, Boeri and Garibaldi (2006).

> 4 See for instance, Rauch (1991), Loayza (1996),  Maloney (1999, 2004), Boeri and Garibaldi (2006), de Paula and Scheinkman (2007), Loayza and Rigolini (2007) postulate a continuum of entrepreneurial ability and workers sorting themselves among different formal and informal sectors of work.

5 The two views are, of course, compatible to some degree given the heterogeneity of the sector, and existing theory can accommodate this: a turnover based efficiency wage model such as that of Stiglitz (1974) allows for firms raising wages above market clearing to deter workers from entering selfemployment and, in the process, creating involuntary informality. The issue is really one of degree- what the “stylized” view of the functioning of the sector should be.

2
loss-to-GDP ratios and country-wide events she found larger impacts. She found the following crucial variables affecting the scale of aggregate effects: structure of the economy and general conditions prevailing, the size of economy, the degree of diversification and the speed of assistance of the international community. Another study, Rasmussen (2004), is in accordance with above studies and for a cross-country sample identified a median reduction of the growth rate by 2.2% points in the year of the event. Raddatz (2007) generally assessed the role of external shocks (such as commodity price fluctuations, natural catastrophe, and adverse influences from an international economic environment) on output volatility of low-income countries. While he found external shocks to explain a fraction of output variance, their contribution to output fluctuations was dwarfed by more important contributors from internal sources such as level of inflation, a possible overvaluation of the real exchange rate and large public deficits. Noy (2009) took a look at the reduction of GDP growth rates for a large sample of disaster events, for which while using a linear regression modeling approach he concluded that the ability to mobilize resources for reconstruction as well as the financial condition of the country are important predictors of GDP growth effects. As one of the few longer term studies, Cuaresma et al. (2004) concluded that the degree of catastrophic risk has a negative effect on knowledge spillovers between industrialized and developing countries. Further, they suggested that only countries with relatively high levels of development may benefit from capital upgrading through trade after a natural catastrophe.

There are only a few studies adopting position 2 and the key papers here are AlbalaBertrand (1993) and to a lesser extent Caselli and Malhotra (2004). In (partial) contrast to the above studies, Albala-Bertrand (1993) came to different conclusions and finds himself partially in opposition to accepted views when analyzing impacts mainly on developing countries. He first statistically analyzed part of the ECLAC data set discussed above and found that natural disasters do not negatively affect GDP, public deficit and inflation in the short to medium term. His findings on the trade deficit are in accordance with ECLAC and other research. These findings he explains with a sharp increase in capital inflows and transfers (private and public donations). He holds that natural disasters do not lower GDP growth rates and "if anything, they might improve them" (1993: 207). Albala-Bertrand also examined longer-term effects for a number of 6
# Improving Air Quality in Metropolitan Mexico City

## An Economic Valuation

### * The Mexico Air Quality Management Team

The Mexico Air Quality Management Team was led by Walter Vergara and includes the following authors: Hennan Cesar' Xander Olsthoomn Victor H. Borja-Aburto<sup>2</sup> Alberto Rosales-Castillo<sup>2</sup> Pablo Cicero-Fernandez<sup>3</sup> Gloria Soto Montes de Oca<sup>4</sup> Kees Dorland' Victor Torres-Meza<sup>2</sup> Roberto Mufioz Cruz<sup>4</sup> Ricardo Uribe Ceron<sup>4</sup> Luke Brander<sup>1</sup> Pieter Van Beukering<sup>t</sup> Maureen Cropper<sup>8</sup> Eduardo Vega L6pez<sup>4</sup> Ana Citlalic Gonzalez Martinez<sup>5</sup> Max Magin Nifio Zarazua<sup>5</sup> Gustavo Olaiz-Fernandez<sup>7</sup> Miguel Angel Nifo Zarazua<sup>5</sup> Ana Patricia Martinez Bolivar<sup>6</sup> Walter Vergara<sup>9</sup> ' Institute for Environmental Studies (IVM), Vrije Universiteit, Amsterdan _2_ Secretaria de Salud, Mexico DF Centro Nacional de Salud Ambiental (CENSA) 3Environmental Health Sciences Department, School of Public Health, University of California Los Angeles (UCLA) _4_ Secretaria del Medio Ambiente del Gobiemo del Distrito Federal, Mexico DF _5_ Unidad Asesora para Comunidades Empresariales, A.C. (UfNACE) _6_ Pan American Health Organization (PAHO) _7_ Direcci6n General de Salud Ambiental, Mexico DF _8_ Development Research Group, World Bank, Washington,

> 9Latin America and Caribbean Environment Department, World Bank

This report is part of a larger study on "Health Risks of Atmospheric Pollution," supervised by the Technical Secretariat of the Environmental Metropolitan Commission. The Institute for Environmental Studies of the Free University (Amsterdam) and the Centro Nacional de Salud Ambiental are in charge of the execution of the report. Copyrights are with the _Comision Ambiental Metropolitana_ (CAM) and the World Bank. This report is part of the assistance provided by the World Bank to the CAM for the formulation of the proposed Third Air Quality Management Plan in the Mexico City Metropolitan Area (MCMA). The assistance also includes technical assistance for the preparation of an updated emissions inventory and for the modelling of the airshed of the MCMA and assessment of measures for air quality improvements. The Netherlands Consultant Trust Fund of the World Bank financed the preparation of the report and the International Development Research Center provided financial support for salaries. The results reported here were managed and supervised by Walter Vergara and Carl-Heinz Mumme. John Dixon and Robert Bacon provided useful comments on drafts of this report.
9 between countries (efficiency-seeking FDI), or as a combination of these two motives. Several studies present findings showing that MNC affiliates that sell (most of) their output in host economy markets are characterized by higher levels of local sourcing (Giroud, Jindra, and Marek,2012; Jindra, Giroud, and Scott-Kennel, 2009; Kiyota et al. 2008). Explanations for this finding include that input requirements and specifications may be less stringent when MNC affiliates produce for host economy markets compared to international markets and that the use of local suppliers makes it easier to adjust products to host economy conditions.<sup>6</sup> When it comes to the impact of the investment motive on technology dissemination and productivity spillovers, findings appear somewhat conflicting. Several studies find that efficiencyseeking MNC affiliates are significantly more supportive of their local suppliers (see, for example, . Gentile-Ludecke and Giroud 2012; Jindra, Giroud, and Scott-Kennel, 2009). Producing for international markets often entails more stringent product requirements and specifications. When efficiencyseeking MNC affiliates use local suppliers, they may be more inclined to offer support to ensure the quality and cost-competitiveness of local inputs. However, various econometric studies find that MNC affiliates that sell (a substantial share of) their output in host economy markets create larger productivity spillovers (see, for example, Syeda 2016; Xu and Sheng 2012; Le and Pomfret 2011). An explanation for this finding is that market-seeking FDI uses more local suppliers, increasing the exposure of domestic firms to modern technologies. Also, it may be that technologies that are used by this type of MNC affiliate are more suited to host economies, facilitating their absorption and application by local firms.

_Mode of entry_ and _percentage of foreign ownership_ . Findings on the effects of these two dimensions are more uniform. MNC affiliates with some level of host economy participation (such as joint ventures) are commonly found to use more local suppliers. Sanchez-Martin, De Pinies, and Antoine (2015) use firm-level data from the World Bank Enterprise Survey (WBES) for a large number of developing countries and identify a negative effect of the percentage of foreign ownership of MNC affiliates on the percentage of inputs sourced in host economies. Wei et al. (2012) and Amendolagine et al. (2019) report a similar negative effect for samples of firms in China, Sub-Saharan Africa, and Vietnam.

> 6 There are recent indications that the effect of the investment motive may be weakening or becoming less clear. One issue is that the level of industry aggregation that is used in studies can affect the classification of MNC affiliates as horizontal or vertical FDI (Alfaro and Charlton 2009). Another issue is that an increasing number of MNC affiliates have both market-seeking and efficiency-seeking characteristics, subject to variation across industries and regions in the world economy (Baldwin and Okuno 2014).
Table 4: Harvests and productivity

||Total harvest<br>($)|Rubber harvest<br>($)|Cocoa harvest<br>($)|Other crops<br>harvest ($)|Total yield<br>($/ha)|Rubber yield<br>($/ha)|Cocoa yield<br>($/ha)|Other crops<br>yield ($/ha)|
|---|---|---|---|---|---|---|---|---|
|Seedling Subsidy|-356.68***|-166.56**|-73.26|-41.87|-32.10*|-29.83**|8.55|-10.63|
||(110.58)|(72.79)|(48.23)|(52.28)|(17.76)|(12.09)|(14.68)|(16.75)|
|Couples' Training|346.05***|180.02**|49.73|54.29|16.74|18.69|-17.65|0.17|
||(132.46)|(85.32)|(61.86)|(57.78)|(19.12)|(15.11)|(17.10)|(15.71)|
|Seedling Subsidy + Couples'<br>Training (beta)|-10.63|13.46|-23.53|12.41|-15.36|-11.14|-9.10|-10.47|
|<br>H0: Seedling Subsidy + Couples'<br>Training = 0 (p-val)|0.93|0.88|0.64|0.79|0.36|0.50|0.52|0.44|
|Observations|1435|1435|1435|1435|1435|1435|1435|1435|
|Mean for control group|1353.01|443.34|480.27|310.55|174.55|78.52|105.88|83.57|
|Mean for individual training|840.80|242.01|351.54|241.06|137.54|51.08|104.98|69.09|

Robust and clustered standard errors in parentheses. All values are winsorized at 99%. Household-level regressions.

* p<0.1 ** p<0.05 *** p<0.01

Note: Baseline control variables in all regressions: Age of household head, Household size, Number of adults, Number of children, Dependency ratio, Married planter, Polygamous relationship, Matrilineal ethnicity, Planter has IGA, Asset index, Credit constrained, Share of plots owned, Average distance to plots (minutes), Number of plots, Average plot size. Contemporaneous control variables in all regressions: Rubber-cocoa intercrop, Any other intercrop.

1
the extent to which these wars are coded as being sustained (as we believe from the narratives that they are), and the correlation over time of whether a country is reported as having a civil war. In econometric terms, the first two properties of the data correspond to errors in variables, and the last property corresponds to autocorrelation in the dependent variable.

The most recent set of data used widely by econometric researchers is the Armed Conflict Dataset of the International Peace Research Institute of Oslo and the Department of Peace and Conflict Research, Uppsala University (hereinafter PRIO/Uppsala), discussed in Gleditsch et al. (2002) and documented in the codebook of Strand et al. (2005). This data set is available in various versions. We do not use the most recent one to remain as consistent as possible with the published studies on which we comment. The codebook defines four types of conflict in which a country can be involved (Strand et al. 2005, 10). Two types of conflict are relevant to our discussion because they are used in econometric studies of civil war: “[type] 3. _Internal armed conflict_ occurs between the government of a state and internal opposition groups without intervention from other states.[type] 4. _Internationalized internal armed conflict_ occurs between the government of a state and internal opposition groups with intervention from other states.” A type 4 conflict is qualified by the variable “location,” which identifies whether the country that is coded as involved in a type 4 conflict experienced violence in its territory. The data set codes each type of conflict into three categories of intensity, of which the first two are “not ordinal”: “1. _Minor_ : At least 25 battle-related deaths per year for every year in the period. 2. _Intermediate_ : More than 25 battle-related deaths per year and a total conflict history of more than 1000 battlerelated deaths, but fewer than 1000 per year. 3. _War_ : At least 1000 battle-related deaths per year” (Strand et al. 2005, 10).

Table 1 presents, in compact form, the entire PRIO/Uppsala data (Version 3) for the 7
- 36 -

Second, the values of the regulated rates were not adjusted during the years of high inflation, thus widening the gap between lending and deposit rates. The wedge between the lending and the deposit rates is explained by the explicit and implicit taxes on banks which are now discussed in greater detail.

# B. Explicit and Impllcit Taxes on Banks

# Explicit Taxes

In contrast to Thailand and Indonesia, where there are no special types of taxes, the Philippines have two types of taxes on the banking industry.

- (a) The Gross Receigt Tax (GRT) is levied on all bank receipts (including both interest and capital gains). GRT is imposed on a sliding scale, with a lower rate applied to income from instruments of longer-term maturity (with a maximum rate being 5 percent). During 1983-86, the GRT added between 73 and 99 basis points to the average intermediation cost.

- (b) Withholding Tax **of** 20 **Percent** is levied on all but overnight deposits (Financial Sector Study, p. v). This tax is a tax on savers which does not result in double taxation and is not very important for our study since it is not a direct tax on financial institutions.

# Implicit Taxes

The instruments of implicit taxation are the requirements for reserves and for specialized loans at low interest rates. Reserves paid only an interest rate of 4 percent and represented an average of 18 percent of deposits, (21 percent of demand and 5 percent of time deposits).
Figure 2: External Links vs. Ownership Integration <!-- Start of picture text --> 3<br>7<br>2.5<br>5<br>2<br>1.5 3<br>1<br>1<br>2014 2015 2016 2017 2018 2019 2020 2021 2022 2014 2015 2016 2017 2018 2019 2020 2021 2022<br>Customer & suppliers Ownership links Customer & suppliers Ownership links<br>Ownership links to agribusinesses Ownership links to agribusinesses<br>2.5 2.5<br>2 2<br>1.5 1.5<br>1 1<br>2014 2015 2016 2017 2018 2019 2020 2021 2022 2014 2015 2016 2017 2018 2019 2020 2021 2022<br>Customer & suppliers Ownership links Customer & suppliers Ownership links<br>Ownership links to agribusinesses Ownership links to agribusinesses<br>US Fortune 500 firms<br>Av. change rel. to firm's 2014 baseline Av. change rel. to firm's 2014 baselineNon-US & US non-Fortune 500 firms<br>US Fortune 500 firms<br>Non-US & US non-Fortune 500 firm<br>Median chg. rel. to firm's 2014 baseline Median chg. rel. to firm's 2014 baseline<br><!-- End of picture text -->

**Note:** This graph compares the evolution of a firm’s number of customers and suppliers to the number of firms that it is linked to via ownership ties (either parent, subsidiary, or common parent). For each firm, the change in the number of externally and internally connected firms is computed relative to its 2014 value, before taking the average over U.S. Fortune 500 agribusiness companies (left graph) and non-U.S. based or non-Fortune 500 U.S. agribusiness companies (right graph). The upper panel shows the yearly average, and the lower panel shows the median relative change to 2014 for the sample of firms. Constantly observed actively covered companies are included. By construction, firms with no ownership links in 2014 are dropped (equivalent for the series depicting relative changes of agribusinesses in a firm’s corporate family).

18
# CONTENTS

|I.|Intro|duction|1|
|---|---|---|---|
|II.|The|Impact of the MFA on Eastern Europe|3|
||(a)|Measures of Restrictiveness|6|
|||EC market|6|
|||US market|11|
||(b)|A Typology of MFA Suppliers|12|
||**(c)**|MFA Quota Growth|14|
|||EC market|14|
|||US market|14|
|III.|"Expe|cted" and Actual Patterns of Specialization|17|
||(a)|The "Expected" Patterns of Specialization|17|
||(b)|The Actual Patterns of Specialization|18|
|||Capital intensity of exports|19|
|||Degree of specialization|23|
|IV.|Concl|uding<br>Remarks|28|
|Refere|nces||31|
|Append|ix Ta|ble|33|
Policy Research Working Paper 8496

# **Abstract**

The paper addresses the issue of the feasible level of private finance in a contracting model of infrastructure funding and financing. It characterizes the structure of financial contracts, deriving the conditions under which both public and private finance coexist. A key feature is that access to outside finance and the regulatory decision on pricing and the amount of public subsidy, hence the extent of price recovery, are jointly determined. Mobilizing private finance requires a combination of price for the service and subsidy to the service provider that is large enough, exacerbating the fundamental tension between financial viability through cost recovery and social inclusion. The paper then shows that the feasibility trade-off responds in non-trivial ways to changes in the economic and institutional environment likely to occur along the development path. While improvements along some of these dimensions, notably in the efficiency of bankruptcy procedures, appear to ease access to private finance, others, such as the cost of public funds, actually makes public finance more efficient. Using project data from the PPI database including information on the financial structure, the authors uncover an inverse U-shaped pattern in the share of private finance, peaking for countries in the upper-middle income range, which echoes their theoretical findings.

This paper is a product of the Climate Change Global Theme. 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/research. The authors may be contacted at mfay@ worldbank.org, david.martimort@parisschoolofeconomics.eu, and stephane.straub@tse-fr.eu.

_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
markets, and they are subject to fixed costs depending on country-pair specific costs (cultural or physical distance) and the policy environment of the host country. We show that the model can rationalize the existence of zero bilateral M&As flows. Moreover, the impact of policy liberalization that reduces the costs of M&As on the probability of observing M&A flows (and on the number of M&A deals) depends on the overall size of the market, the composition of the GDP, and the extent of inter-sectoral linkages. We label the possibility that the effect of a given policy on a certain outcome variable might depend on the state of the world in which the policy is applied _state-dependency in policy effectiveness_ .

Third, inspired by the model, we undertake a two-stage empirical analysis. In the first stage, we estimate a Probit model using bilateral M&A data. The Probit includes host country and home country fixed effects, physical distance and proxies for the cultural distance between countries. In the second stage, we investigate the determinants of host country fixed effects, in particular the role of policy barriers towards M&A. We repeat the analysis also using the total number of M&A deals flowing to different service sectors in individual countries, thus exploring the intensive margin. Following Santos-Silva and Tenreyro (2006), we use in this case a pseudo-maximum likelihood (PPML) estimator for the first stage. Our findings are the following: (1) Geographical barriers affect M&A in services and manufacturing similarly, but cultural barriers affect M&A in services more than in manufacturing. Both types of barriers have heterogeneous effects across services sectors: a shared border matters more in transportation, as expected, but also in retail; and a common language is more important for M&A in telecommunications, as well as in banking and insurance. (2) Across countries, the probability of receiving investment through cross-border M&A is strongly positively correlated with market size. Restrictive policy dampens M&A inflows but the negative effect of policy is mitigated in countries with a relatively large shares of manufacturing and (to a lesser extent) services in GDP. The same results hold for the total number of M&A deals received. These findings suggest that the _impact of policy is statedependent_ and related to the composition of the GDP of the target country. The results may help explain why policy restrictions have inhibited services investment in the industrializing 3