rafmacalaba/datause-encoder-data huggingface dataset:
this innovation inevitably pass through to consumers, who ultimately fund the technological development. High-income households more frequently purchase new vehicles that are also more expensive, thus incurring a larger share of these costs. This has sometimes been used as an argument for the progressivity of instruments on purchase. Indeed, considering only the impact on the market for new cars, such the CAFE standards have been found to be progressive. However, if the analysis accounts for the propagation of price impacts to the used car market, the distributional impact becomes regressive (Jacobsen, 2013; Davis & Knittel, 2019). Additionally, instruments on purchase based on fuel economy subsidize high fuel economy vehicles, either implicitly through standards or explicitly through feebate schemes. Efficient vehicles are generally more expensive and more often purchased by high-income households. Conversely, inefficient vehicles are generally cheaper and more often purchased by low-income households. These consumption patterns tend to further exacerbate the regressivity of price instruments on purchase based around fuel economy (West, 2004).

International evidence underlines the context-dependent nature of distributional impacts. Although possibly more nuanced, the findings above may be specific to the US. Examining the international evidence underlines the dependency on local income, spatial development, and car use patterns. A study of fuel taxation across seven countries in Europe, namely France, Germany, United Kingdom, Italy, Serbia, Spain, and Sweden, found that their distributional impacts were approximately proportional, i.e., neither progressive nor regressive (Sterner, 2012). The largest outlier is Serbia, for whom fuel taxation is relatively more progressive. Notably, Serbia is the lowest income country in the sample. An evaluation of fuel taxes in Brazil also found the distributional impacts to be progressive (Proque et al., 2022). These findings align with the intuition that taxation of private vehicles and their use is progressive in lower income countries, where cars remain more of a luxury good. However, as countries become richer, cars become more ubiquitous, and taxation of private vehicles becomes increasingly regressive (Berri et al., 2014). The distributional impacts also depend on which and how externalities are accounted for. In Sweden, a study found that people in rural areas are far more adversely affected by motor taxes than in urban areas. These distributional differences were not counterbalanced by various recycling schemes (Eliasson et al, 2018). In France, a feebate scheme introduced in 2008 encouraged adoption of diesel over gasoline vehicles. Diesel engines emit fewer GHG emissions but more local air pollutants. In other words, the policy changed the distribution of externalities 18
measures may provide an important complement to individual actions in reducing farmers’ exposure to pesticide hazards.

# **References**

- Chung, D. K. and K. T. Dung. 2002. _Pest Management in Rice Production in Vietnam: A Socio-economic Assessment_ . Hanoi: Nha Xuat Ban Nong Nghiep.

- Cropper, M. 1994. Economic and Health Consequences of Pesticide Use in Developing Country Agriculture: Discussion. _American Journal of Agricultural Economics_ 76: 605-607.

- Du, L. N. T. and N. T. Phoung. 2003. Real Situation of Preservation, Use and Residues of Pesticides in Honey Grass in An Vy, Khoai Chau, Hung Yen province. The 1<sup>st</sup> International Scientific Conference, Hanoi, Vietnam, pp. 275.

- Extension Toxicology Network (ECOTOXNET). 2004. Cholinesterase Inhibition. Toxicology Information Brief. Cornell University.  Available at: <u>http://pmep.cce.cornell.edu/profiles/extoxnet/TIB/cholinesterase.html</u>

- FAO. 2001. Farmer Self-Surveillance of Pesticide Poisoning Episodes: Report on One Month Pilot: August 15-Sept 15, 2000. FAO Programme for Community IPM in Asia, Field Document.

- FAO. 2004.  FAO-STAT.  Statistics downloaded for Vietnam.  Available at: <u>http://apps.fao.org/default.jsp.</u>

- Hon Tu, N. _et al_ . (1999) Report of investigation for working condition and female workers' health in agricultural production. Ministry of Health **,** Hanoi.

- Huan, N. H. and L. V. Thiet et al., 2000. Results of Survey for Confidence, Attitude and Practices in Safe and Effective Use of Pesticides.

- Kishi, M., N. Hirschhorn, M. Qjajadisastra, L. N. Satterlee, S. Strowman and R. Dilts. 1995. Relationship of Pesticide Spraying to Signs and Symptoms in Indonesian Farmers. _Scandinavian Journal of Work & Environmental Health_ 21: 124-133.

- Pimental, D., Acquay H., Biltonen, M., 1992. Environmental and Economic Costs of Pesticide Use. _Bioscience_ 42, 750-60.

- Pincus, J. 1995. _Pesticide Policy Survey._ Unfinished report. FAO Intercountry Programme for IPM in Rice in South and Southeast Asia, Hanoi.

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17 City has grown dramatically in the past several decades; there were approximately 48,000 cars in 1940, 680,000 in 1970, 1.1 million in 1975 and 2.6 million in 1989. The Mexican government estimates that fewer than half of these cars are fitted with even modest pollution control devices. Virtually none are equipped with state-of-the-art exhaust treatment systems. Only recently has unleaded gasoline become available. The lead content of leaded gasoline was lowered during 1986 and 1987, but there are indications that it has increased since then [Walsh 1989b].

In addition, more than 40% of the cars are over 12 years old, and of these, most have engines in need of major repairs. The degree to which the existing vehicles are in need of maintenance is reflected by the results of the "voluntary" inspection and maintenance program run by the Federal District during 1986 through 1988. Of the over 600,000 vehicles tested (209,638 in 1986, 313,720 in 1987 and 80,405 in the first four months of 1988), about 70% failed the gasoline vehicle standards and 85 % failed the diesel standards.

Although there are not as many commercial vehicles as automobiles in Mexico City, they are considered a serious pollution hazard because of the high levels of fine particles produced by diesel engines and the direct public exposure to these emissions. The contribution of mobile and stationary sources to emissions of primary air pollutants in Mexico City is summarized in Table _5;_ motor vehicles contribute the preponderant part of CO, HC, and NOx emissions.

**Table 5. Source distribution of air pollutant emissions in Mexico City, 1987**

|**Pollutant**<br>**Total**||**Distrib**|**ution by**|**Source**|**(%)**|||
|---|---|---|---|---|---|---|---|
|**Emissions**||M|otor Ve|hicles||Industry|Natural|
|**(tons/year)**|**Cars**|**Taxis**|**Buses**|**Trucks**|**Total**||**Sources**|
|**CO**<br>3,549,000|54|13|1|31|99|1|0|
|HC<br>335,000|61|14|1|13|89|11|0|
|NOx<br>270,000|34|8|3|19|64|36|0|
|S02<br>445,000|0|0|0|2|2|98|0|
|Particulates<br>428,000|0|0|1|8|9|30|61|

Source: [Joumard 1989] Despite the rapid growth in motor vehicles in Greater Mexico City over the last several decades, the number of cars licensed in the Federal District (city center) has stabilized since 1980, and the number of trucks and buses seems to have decreased slightly. This is probably to be expected at the center of a very large conurbation and follows the trend in other large cities, where a stage is reached after which the increase in vehicle population takes place largely in surrounding districts. In the metropolitan zone, outside the Federal District, the vehicle
Policy Research Working Paper 7214

# **Abstract**

The economic debate on existence and definition of the middle class has become particularly lively in many developing countries. Despite this growing interest, the identification of the middle class group in these countries remains quite challenging. Building on a recently developed framework to define the middle class, this paper tries to estimate the Nigerian middle class size in a rigorous quantitative manner. By exploiting publicly available panel data, the expenditure associated to a 10 percent probability of falling into poverty is estimated, and this is used as the middle class threshold for Nigeria. The threshold expenditure for the middle class in Nigeria is found to be 378.39 Naira per capita per day (2010 PPP). Relying on this threshold and through survey-to-survey imputation the size of Nigeria’s middle class in 2003 is also estimated. The results show that there has been considerable improvement on the size of the middle class and poverty reduction between 2003 and 2013. Poverty decreased between 2003 and 2013 from 45 to 33 percent, while the middle class increased from 13 percent to 19 percent. Nevertheless the results still paint a heterogeneous picture of poverty and the middle class in Nigeria, where the largest portion of the population, although above the poverty threshold, continues to live with average or high vulnerability to poverty.

This paper is a product of the Poverty Global Practice 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 vmolini@ 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
INTRODUCnON XXi The estimates assign to the United States more net immigrants in 1985-90 than all other countries of the world combined. Other major destination countries are Australia, Saudi Arabia, Canada, and Cote d'Ivoire. Mexico has by far the largest net emigration, and its dominance in this area is expected to increase in the 1990s.

# SUMMARY OF RESULTS

A brief discussion of projection results in this section will focus, first, on the population of the world and continents; secord, on the population of subcontinental geographic regions and of countries grouped by income; third, on the population in World Bank regions, which differ from the U.N. geographic regions; and, finally, on the population of particular countries or economies.

# _World and Continents_

For the world and the continents, we consider population totals and medium-term growth; long-run growth; age structure and dependency, and the fertility and mortality rates underlying the projections.

World population. The population of the world is estimated at 4.84 billion in 1985. It surpassed 5.0 billion in mid-1987, and is projected to reach 5.3 billion in 1990 (Table 4). The annual rate of growth in 1985-90 has been 1.74 percent. TIis rate is projected to decline to 1.66 percent in the first half of the 1990s, and to 1.54 percent toward 2000. In spite of this, the annual net increase in the number of people will be larger each year until the late 1990s, averaging Table 4 Total Population, Annual Increase, and Growth Rates for the World and Less Developed and More Developed Countries, 1985-2025

||Popula|tion (millio|ns)||Annual i|ncrease<br>(m|<br>illions)|<br>Growt|h<br>rate (pe|rcent)|
|---|---|---|---|---|---|---|---|---|---|---|
|||Less|More|||Less|More||Less|More|
|Year|<br>World<br>d|<br>evelope**d**|eveloped|Period|World d|evetoped<br>d|<br>eveloped|World<br>d|<br>eveloped<br>d|<br>eveloped|
|1985|<br>4,844|<br>3,666|<br>1.179|1985-1990|<br>88.2|81.7|6.5|1.74|2.11|0.54|
|1990|<br>5.285|<br>4,074|<br>1,211|1990-1995|<br>91.7|85.9|5.8|1.66|2.00|0.47|
|1995|<br>5,744|4,504|<br>1,240|1995-2000|<br>92.1|87.0|5.1|1.54|1.84|<br>0.41|
|2000|<br>6,204|<br>4,939|<br>1,265|2000-2005|<br>91.7|87.4|4.3|1.43|1.70|<br>0.34|
|2005|<br>6,663|<br>5,376|<br>1,287|2005-2010|<br>89.9|86.4|3.5|1.31|1.55|0.27|
|2010|<br>7,112|<br>5,808|<br>1,304|2010-2015|<br>88.7|85.7|2.9|1.21|1.42|<br>0.22|
|2015|<br>7,556|<br>6,237|<br>1,319|2015-2020|<br>87.5|85.3|2.1|1.13|1.32|<br>0.16|
|2020|<br>7,993|6 663|1,330|2020-2025|<br>84.4|83.0|1.4|1.03|1.21|<br>0.10|
|2025|<br>8,415|<br>7,078|<br>1,336||||||||

Note: "More developed" comprises Europe, U.S.S.R., Northern America (United States and Canada), Australia, New 2ealand, and Japan. "Less developed" comprises the rest of the world.
The major problem with such macro-econometric models is that they are subject to the well-known Lucas critique (Lucas 1976). The models are identified based on historical correlations in macroeconomic data, and because such correlations are not fundamental structural parameters, they may well change when policy changes. Thus, although such models can be useful for forecasting, especially in the short run, they are not well suited to analyzing the long-term effects of policy changes. Consequently, over the past few decades, there has been a strong movement in macroeconomics away from using such models for policy analysis.

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# **Table 11: Correlates of FDI Flows**

|||**FDI I**<br>|**nflows**<br>|||**FDI O**<br>|**utflows**<br>||
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Federal Funds Rate|0.008|0.038**|0.022|0.044|-0.090***|-0.061***|-0.080***|-0.063*|
||[0.39]|[2.12]|[0.97]|[1.50]|[4.35]|[3.02]|[3.38]|[1.90]|
|Log(VIX)|0.020|-0.082|0.023|-0.023|-0.142|-0.215**|-0.152*|-0.155|
||[0.21]|[0.88]|[0.25]|[0.23]|[1.63]|[2.58]|[1.78]|[1.61]|
|GDP growth|0.035***|0.025***|0.034***|0.040***|0.019***|0.012**|0.017**|0.024***|
||[3.72]|[3.10]|[3.67]|[3.84]|[2.83]|[2.19]|[2.41]|[3.23]|
|Investment environment||0.168***||||0.138***|||
|||[6.09]||||[5.91]|||
|Chinn-Ito index of capital account openness|||0.191***||||0.115**||
||||[4.52]||||[2.15]||
|Bank assets, % of GDP||||0.023***||||0.016***|
|||||[5.02]||||[3.07]|
|Country fixed-effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Observations|2,256|2,234|2,148|2,001|2,256|2,234|2,148|2,001|
|R-squared|0.023|0.071|0.049|0.094|0.039|0.069|0.049|0.086|
|# of countries|29|29|29|29|29|29|29|29|

_Notes:_ The dependent variable is FDI inflows as % of trend GDP, in Columns 1-4 and FDI outflows as % of trend GDP in Columns 5-8. The dependent variables are standardized by subtracting the country-specific mean and dividing by the country-specific standard deviation. The sample spans from 1990:Q1 to 2015:Q4. Robust t- statistics are reported in brackets. ***, **, * indicate significance at the 1%, 5% and 10% level.

21
2 regime followed the real exchange rate has shown a relatively high degree of stability. This is in contrast with the experience of the vast majority of the rest of the developing world where commercial policies have usually taxed exports and maintained their real exchange rate overvalued for periods of time, which in turn have forced periodic balance of payments crises and a high degree of instability of the real exchange rate.

The above evidence is, of course, only suggestive. It is possible that these particular policy differentials make no real difference and that the apparent correlation between policy and growth have no causal implications. Nonetheless, there exists some further evidence obtained by detailed, usually multicountry studies, which despite their many limitations still point towards some degree of a systematic relationship between trade policy orientation and growth.' Several studies have been directed to either endogenize productivity growth by making it dependent on the trade regime, or to remove the assumption of constant returns to scale thus allowing for internal or external economies of scale. Two other mechanisms by which trade/macro policies can affect growth at least in the intermediate run, which have received little attention are the following: (i) the effect of economic instability (in particular exchange rate instability) on productivity growth that exante unsustainable trade/macro policies may generate, and (ii) the effects of these policies on capital accumulation. Unsustainable strategies are those that follow a combination of macro and trade policies that are not consistent with external (current account) equilibrium. Ex-ante unsustainable strategies lead to economic instability characterized by periodical balance of payment crises that force major adjustments of the exchange rate and domestic expenditures. Once the crisis is ov-r the policy mix becomes again biased by taxing exportables and importables. This, in turn, causes more external disequilibria which after a while require a new round of devaluation and expenditure adjustment. Although both sustainable and unsustainable strategies are characterized by external equilibrium on average over a long period of I See Edwards (1989) for a critical review of the empirical studies available.
Deininger, K., L. Squire, and S. Basu. 1998. “Does Economic Analysis Improve the Quality of Foreign Assistance?” _World Bank Economic Review_ 12 (3): 385–418.

Dhaliwal, I., and C. Tulloch. 2012. “From Research to Policy: Using Evidence from Impact Evaluations to Inform Development Policy.” _Journal of Development Effectiveness_ 4 (4): 515–36.

Friedman, J. M., M. Vledder, M. Sjoblom, and P. Yadav. Forthcoming. “Improving Patient Access to Malaria and Other Essential Medicines in Zambia: Results of a Pilot Project.” Presented at the Transport Learning Event, Washington, DC, 2010.

http://siteresources.worldbank.org/INTTRANSPORT/Resources/3362911297096897336/7715763-1297096948414/Presentation-Friedman.pdf.

Ika, L. A., A. Diallo, and D. Thuillier. 2012. “Critical Success Factors for World Bank Projects: An Empirical Investigation.” _International Journal of Project Management_ 30 (1): 105–16.

Kilby, C. 2000. “Supervision and Performance: The Case of World Bank Projects.” _Journal of Development Economics_ 62 (1): 233–59.

Kilby, C. 2011. “Assessing the Contribution of Donor Agencies to Aid Effectiveness: The Impact of World Bank Preparation on Project Outcomes.” Villanova School of Business Economics Working Paper 20, Villanova University, Pennsylvania.

Kilby, C. 2013a. “The Political Economy of Project Preparation: An Empirical Analysis of World Bank Projects.” _Journal of Development Economics_ 105:211–25.

Kilby, C. 2013b. “An Empirical Assessment of Informal Influence in the World Bank.” _Economic Development and Cultural Change_ 61 (2): 431–64.

Kondylis, F., M. Jones, and D. Stein. 2014. “Commitment, Mental Accounting, & Agricultural Investment: Evidence from Rwanda.” Mimeo. World Bank Legovini, A. 2010. “Development Impact Evaluation Initiative: A World Bank–Wide Strategic Approach to Enhance Developmental Effectiveness.” World Bank, Washington, DC. http://siteresources.worldbank.org/INTDEVIMPEVAINI/Resources/39981991286546178578/7465778-1291306572028/Legovini_dime_paper_ext.pdf.

Legovini, A. 2011. “DIME Progress Report.”, World Bank, Washington, DC. http://siteresources.worldbank.org/INTDEVIMPEVAINI/Resources/39981991372170088287/DIME_progress_report_2012.pdf.

Legovini, A., and G. Bedoya. 2014. “Dime’s Current Portfolio and Approach to Impact Evaluation.” Technical note, World Bank, Washington, DC.

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7 Besides certain obvious risks (political instability, low liquidity, unreliable information, insider trading, exchange rate risk<sup>3</sup> , etc.) emerging stock markets tend to be risky for other reasons related to their economic and market structure. Unlike developed markets which have diverse sectors that are differently affected by market shocks, emerging markets because of less diversified industrial bases are more susceptible to macroeconomic shocks. Also, because of low liquidity, the stock markets in these countries tend to be concentrated in a few large stocks. These factors tend to accentuate market shocks.

The volatility of emerging markets should, however, be balanced against the fact that these markets exhibit very low or negative correlations with the less risky developed markets. Thus, portfolios composed of stocks from developed and emerging markets offer significant risk diversification potential.

We constructed an international portfolio of 14 assets. Besides commodity market investments, as represented by the GSCI, we chose stocks from developed and emerging markets. Among the developed markets we chose the United States, United Kingdom, Japan, Germany, Switzerland, France, and Hong-Kong. From the emerging markets we chose Taiwan, Korea, Mexico, Thailand, Brazil, and India<sup>4</sup> . Table 2 reports monthly average returns (in 3Exchange rate risk may, however, not be a significant issue in international investment. Solnik and Noetzlin (1982) found exchange rate risk for stocks of developed markets to be a small part of aggregate investment risk and Errunza and Losq (1987) found a similar result for emerging markets. The insignificance of the currency factor is due to the fact that currency volatility and stock market volatility are generally weakly or negatively correlated.

4The data for the developed markets is from the MSCI (Morgan-Stanley Capital Markets International) index and the data for the emerging markets is from the IFC (International Financial Corporation) Emerging Markets Database. We chose the emerging markets on the basis of both risk diversification potential and market liquidity. We used market capitalization as an indicator of the latter.