rafmacalaba/datause-encoder-data huggingface dataset:
we initially define the spatial extent of these cities using nightlights. Within these light boundaries, we restrict attention to 40-meter pixels defined as built-up in 2014 according to the Global Human Settlements Layer (ghsl) of the European Commission’s Joint Research Centre (jrc). After dropping cities for which no appropriate light exists, aggregating multiple cities within the same contiguous light, and dropping cities for which the relevant ghsl data are missing, we are left with an estimation sample of 154.

# **_2.2 Trips data_**

We define a _trip_ as a pair of points (origin and destination) within the same city as defined above. A _trip instance_ is a trip taken at a specific time. Our target sample for city _c_ is 15 � _Popc_ trips, where _Popc_ is the projected 2015 population of city _c_ from United Nations (2015), and 10 trip instances per trip, to ensure variation across times of day. For a city of population, say, one million, our sampling strategy thus targets 15,000 trips and 150,000 trip instances. Our sampling strategy is symmetrical, in the sense that each trip from origin _o_ to destination _d_ has a counterpart trip from origin _d_ to destination _o_ .<sup>9</sup> All trips are restricted to be at least one kilometer between origin and destination because Google results are less reliable for very short trips, few of which we expect to be motorized anyway. We sample across times of day to roughly match the weekday distribution of actual trips in Bogotá from Akbar and Duranton (2018). We oversample sparse overnight periods, and sample weekends at half the rate of weekdays.

We sample across four broad classes of trips, each designed to reflect key aspects of urban travel: radial, circumferential, gravity, and amenity trips.

Radial trips join a randomly located point within 1.5 kilometers of a city’s center (as defined by United Nations, 2015) with another point in the city, either approximately 2, 5, 10, or 15 kilometers away, or at a distance percentile drawn from a uniform distribution. These trips are those predicted by the standard monocentric model of cities (Alonso, 1964, Mills, 1967, Muth, 1969). This models a reasonable first-order characterization of the distribution of population, density, and land and house prices in cities of many countries (see Duranton and Puga, 2015, for a survey).

Circumferential trips, orthogonal to radial trips, join a randomly located origin at least 2 kilometers from the city center with a destination at approximately the same radius but

> 9Unless otherwise indicated, random points are drawn with uniform probability from a support that is all valid 40-meter pixels within a city as defined above.

4
# Appendix: A.1. Incidences of Missing Observations of Used Variables

|_Variables_|_Incidence of missing_<br>_observation (_**_%).:_**|
|---|---|
|Firm age<br>|3.5|
|Input price index of the firm<sup>25</sup>|16.9|
|Job mix of engineers, workers, and management personnel|10.0|
|Marginal profit retention rate|59.6|
|W_ELASTICITY<br>|_2.5_|
|_S_PLANQUAN:_share of output under the mandatory plan of the government<sup>26</sup>|33.7|

## **Reference**

- Bahk, Byong-Hyong, and Michael Gort, "Decomposing Learning by Doing in New Plants," _Journal of Political Economy,_ 101 (1993), 561-83.

- Barberis, Nicholas, Maxim Boycko, Andrei Shleifer, and Natalia Tsukanova, "How does Privatization Work? Evidence from the Russian Shops," _The Journal of Political Economy,_ 104(4), 764-90, August 1996.

- Boardman, Anthony, and Aidan R. Vining, "Ownership and Performance in Competitive Environments: a Comparison of the Performance of Private, Mixed, and State-Owned Enterprises," _Journal of Law and Economics,_ April 1989, 32, 1-33.

- Boycko, Maxim, Andrei Shleifer, and Robert W. Vishney, "Property Rights, Soft Budget Constraints, and Privatization." Memeo., Harvard University, 1994.

- Coase, Ronald, "The Institutional Structure of Production," The Nobel Prize Lecture, delivered December 9, 1991, in Stockholm, Sweden.

- Demsetz, Harold, _Ownership, Control And The Firm,New_ York: Basil Blackwell, 1988.

- Dong, Furen, "Behavior of China's State-owned Enterprises Under the Dual System," _Caomao Jingii_ (Finance and Economics), 9 (1992), 3-15.

- Ehrlich, Isaac, George Gallais-Hamonno, Zhiqiang Liu, and Randall Lutter. "Productivity Growth and Firm Ownership: An Analytical and Empirical Investigation," _Journal of Political Economy,_ 102 (1994), 1006-1038.

- Greene, William, _Econometric Analysis,_ New York: Macmillan, 1990.

- Groves, Theodore, Yongmiao Hong, John McMillan, and Barry Naughton, "Autonomy and Incentives in Chinese State Enterprises," _Quarterly Journal of Economics,_ 109 (1994), 181-209.

- Groves, Theodore, Yongmiao Hong, John McMillan, and Barry Naughton, "China's evolving managerial labor market," forthcoming in _Journal of Political Economy,_ August 1995.

- Grossman, Sanford J., and Oliver D. Hart, "The cost and Benefits of Ownership: a Theory of Vertical and Lateral Integration," _Journal of Political Economy,_ 90 (1986), 691-719.

25This is observed only after 1984. The missing incidence for this variable refers to that after 1984. 26This is observed only after 1983. The missing incidence for this variable refers to that after 1983.

31
Thomas, Duncan (1997) Incomes, expenditures and health outcomes: Evidence on intrahousehold resource allocation. In Lawrence James Haddad, John Hoddinott, & Harold Alderman (Eds.), Intra-household resource allocation in developing countries: Models, methods and policy. Baltimore, MD: The Johns Hopkins Press.

United Nations Development Programme UNDP (1995) Human Development Report 1995. Gender and Human Development. New York: Oxford University Press.

United Nations Development Programme UNDP (2010) Human Development Report 2010. The Real Wealth of Nations: Pathways to Human Development. New York: Palgrave Macmillan.

World Bank (2011) World Development Report 2012: Gender Equality and Development. Washington, DC: World Bank.

25
analyze the results of the Monte Carlo simulations. First, there is the potential issue of misspecification of the econometric model, Equation (1). The econometric specification of mean income growth could be affected by omitted factors: global and country-specific components. Additionally, some of the factors affecting mean income growth might not respond to a linear form.

Second, the probability distribution assumptions may affect the variables used to predict the future behavior of the country mean income growth. Global growth and commodity prices could entail more complicated distributions with longer tails. In the same vein, the idiosyncratic error terms could have a long-tailed distribution or skewed parameterization instead of a normal distribution arrangement. Thus, our projections of mean income growth may not capture tail behaviors. In the same vein, given a lack of observations for the Gini coefficient across countries over the study period 1980–2014, the bounded random walk stochastic process assumption that models the logarithm of the Gini coefficient could entail a very restrictive specification.

Third, country-level statistics are based on household data that incorporate multiple sources of errors. For instance, collected household observations could include sampling and non-sampling measurement errors. Although the number of household surveys has expanded in countries around the world, the frequency and quality of the collected information vary greatly, which may cause problems related to the consistency and comparability of the data between and within countries (World Bank 2014, Chapter 5). Fourth, demographic trends that account for changes in the total population might have some degree of uncertainty, especially in terms of the materialization of a significant factor such as war, massive migration, or an epidemic (United Nations 2017).

# **VI. RESULTS**

This section presents our simulated outcomes of poverty and changes in the income distribution for the period 2015–2030. All our results are analyzed at the global level and by the country typologies introduced in Table 1. Subsections A and B discuss poverty headcount and relative income inequality estimates, respectively. In Subsection C, we analyze the speeds of the B40  percent relative to other percentile growth rates of the income distribution shared prosperity Page **18** of **45**
2

# **1 Debate on poverty lines**

Recent evidence for Mozambique has re-opened the debate on the choice for a poverty line suitable for national poverty assessments (MPD-DNEAP, 2010; Arndt and Simler, 2010; Boom 2011; Alfani et al 2012; Boom et al., 2012). The choice is between a single national poverty line and a contextspecific poverty line (CSPL) that is adapted to locally observed consumption and price patterns.

Whether a national poverty line or a CSPL is the preferred approach is an important question, because opting for either of the two tends to have important implications for poverty assessments and targeting. For example, in a seminal article on the subject for Indonesia, Ravallion and Bidani (1994) compare a CSPL that is adjusted to rural and urban consumption with a national line that is the same for rural and urban poor alike. Among others, they find that rural poverty exceeds urban poverty under the national poverty line (respective headcount of 24% and 11%) but, surprisingly, the rural-urban gap completely disappears under the context-specific poverty line. Rural poverty even becomes lower than urban poverty (respective headcount of 14% and 17%), an effect due to a far higher urban poverty line. A similar drastic impact is found in a recent paper on Congo, where the comparison of a national line with a CSPL implies: “ _instead of being twice as high, the welfare level of urban dwellers seems to be barely 6 percent higher on average compared to the welfare level of their rural compatriots_ " (Marivoet and De Herdt, 2103:19).

By the same token, trends can be extremely responsive to the poverty line. For example, using a CSPL that is adapted to the consumption and the prices in 13 different regions of Mozambique, the reduction of poverty in during 1997-2003 and 2003-2009 is entirely concentrated in the first period with a spectacular decrease from 70% to 54%, while there is a slight upward trend in poverty in the second period, with a small and fluctuating urban-rural gap of 10, 4 and 7 percentage points in the respective years 1997, 2003 and 2009 (MPD-DNEAP, 2010). Under a national line, poverty came also down in the first period, though less spectacularly from 70% to 61%, while continuing to decrease to 57%, with a large rural-urban gap that shows a consistent decline from 34 to 31 to 26 percent points in the respective years (Boom et al., 2012).

The appeal of a CSPL is that it may accommodate for substitution behavior and heterogeneity of preferences. In standard microeconomics, a household can adapt to the price vector by substituting away from expensive items in an effort to maintain the same utility (revealed preferences). Likewise, two households with the same preferences can consume different bundles in response to local market
# **6.1 Plausible Mechanisms**

Several plausible mechanisms can explain the improvement in health, cognition, and labor market outcomes due to exposure to a village midwife early in life. First, a number of studies find that the midwife programs are associated with greater antenatal and postnatal care (Frankenberg et al., 2009; Rao, 2014). Accordingly, the effect of the program on antenatal care is investigated. Here, the panel feature of the IFLS is particularly advantageous, as it gives information on the receipt of such inputs for individuals who were exposed to the program early in life and then were interviewed in 2014.<sup>34</sup> Table 6 shows the mean effect of the program expansion on three outcomes: use of antenatal care, skilled delivery at birth, and one postnatal input, breastfeeding. While all the regressions control for birth year fixed effects and community fixed effects, the last four columns additionally control for province-specific linear trends. Column (1) of Table 6 shows the effect on the use of antenatal care—individuals who were exposed to the midwife program during pregnancy were 10 percent more likely to receive antenatal care compared to individuals who were not exposed to the program during pregnancy or exposed during their first four years of life. In the same table, column (2) shows the effect on attendance of midwife during birth. Individuals exposed to the program are more likely to be attended by a midwife during their birth. Finally, there are no effects of the midwife program on breastfeeding practices for any group.<sup>35</sup><sup>_,_36</sup> The results are very similar when both province-specific linear trends and 1983 district health facilities interacted with year of birth

> 34In this case, a slightly different econometric specification is used than in equation (1)–the children who are exposed at age 1-3 and age 4 are treated as controls and everything else is same as the main specification. The reason is that many of the mechanisms involve outcomes such as birth weight, antenatal care, and attendance of midwife during birth which are available only in the last five years from the survey (birth cohorts born between 1989 and 1994). Therefore, including cohorts with exposure to _in utero_ , between age 1 and 3 years, and age 4 years together will not produce enough variation. Given that the program is not going to affect these mechanism outcomes for children who are exposed to the program during 1-4 years after birth, one can treat them as controls and focus on the program’s impact on those who were exposed _in utero_ .

> 35Information from the first two waves of the IFLS is used. Using the information from the third wave in the IFLS, Frankenberg et al. (2009) confirm that the placement of village midwives in communities is associated with significant increases in a woman’s receipt of iron tablets and in her choices about care during delivery.

> 36Because of the unavailability of information in the first wave of the IFLS, the impact of midwives on other postnatal investments, including vaccination and micro-nutrient supplementation (other than breastfeeding), could not be explored.

17
# REFERENCES

Baffo, Robert. 1991. "Economic Growth in a Cross Section of Countries." Quarterly Journal of Economic, 106(1) :407-443.

Barro, Robert J. And J.W. Lee. 1994. "Losers and Winners in Economic Growth." Proceedings of the World Bank Annual Conference on Development Economics 1993. Washington, D.C: World Bank.

Barro, Robert and J.W. Lee, 1997. "International Measures of Schooling Years and Schooling Quality," AER, Papers and Proceedings, 86(2), pp. 218-223.

Becker, Gary S. 1964. Human Capital. New York: Columbia University Press.

Behrman, Jere. 1987. "Schooling in developing countries: Which countries are the over and underachievers and what is schooling impact?" Economics of Education Review, 6(2): 111-127.

Behrman, Jere and Nancy Birdsall. 1983. "The Quality of Schooling, Quantity Alone is Misleading." American Economic Review, 73(5):928-946.

Ben-David,D.,and M., Loewy. 1995. "Free Trade and Long Run Growth." CEPR working paper 1183.

Benhabib, Jess and Mark Spiegel. 1994. "The Role of Human Capital in Economic Development: Evidence from Cross National Aggregate Data." Journal of Monetary Economics.

Coe, D., and E. Helpman. 1993. International R&D Spillovers, NBER working paper 4444.

Cohen, S. 1. 1985. " A Cost-Benefit Analysis of Industrial Training." Economics of Education Review 4(4):327-39.

Dasgupta, Partha, and Joseph Stiglitz. 1988. "Learning-by-doing, Market Structure, and Industrial and Trade Policies." Oxford Economic Papers 40 (1988):246-68.

Dasgupta, Partha, and Martin Weale. 1992. "On measuring the quality of life." World Development. 20(1): 119-131.

de Gregorio, Jose. 1992?. Growth in Latin America. Journal of Development Economics. vol.31 no. 1 pp.59-84.

de Long, Bradford, and Lawrence Summers. 1993. "How Robust Is the Growth-Machinery Nexus?" Paper presented at the conference How Do National Policies Affect Long-run Growth? The World Bank, Washington, D.C: February.

. 1991. "Equipment Investment and Economic Growth." Quarterly Journal of Economics, May.p.445-502.

de Melo, Jaime and Sherman Robinson. 1990. "Productivity and Externalities: Models of Export-led Growth." Policy Research Working Paper 387. World Bank, International Economics Department International Trade Division, Washington, D.C.

Denison, E.F. 1962. Sources of Economic Growth In the United States and the Alternative Before Us. New York: Committee for Economic Development 23
consumption is also a function of initial assets and household labor endowments, we include baseline household demographics, the community wage rate and head and spouse characteristics, i.e. the _Xij,97 17_ . As before, the error term is composed of an idiosyncratic disturbance, ξ _ijt_ , and a community random effect, _vj_ .

The specification in (9) allows us to identify the marginal propensity to consume and the increase in consumption from investment. The marginal propensity to consume, _α,_ is just the coefficient on current transfers, φ _1_ . The rate of return in terms of increased income, γ, is φ 2 φ 1 ( 1 −φ 1 ) , where φ _2_ is the coefficient on lagged transfers, and the rate of return in terms of consumption is φ 2 (<sup>1</sup> −<sup>φ</sup> 1 ) .

# **4.2 Estimated Treatment Effects**

We now turn to the analysis of the effects of current and lagged cumulative transfers on consumption. Our aim here is to determine the proportion of the cash transfer that is consumed directly out of current transfers, with the remainder being saved or invested. We then capture the long run effects of the program on consumption through the total cumulative transfer amount lagged by 6 months, and argue that any increased long run consumption is achieved through productive investments.

We estimate (9) for the 4 rounds of the ENCEL for which we have detailed consumption information, including home produced consumption. As has been previously discussed, because reception of the transfer is conditional on school enrollment, the transfer amount received is endogenous to household behavior. Thus, we instrument current and lagged actual transfers with their “potential” counterparts<sup>18</sup> . The standard errors are clustered at the community level to control for the correlation of the productivity shocks within communities over time.

> 17 The full list of controls is kept the same as for the investment runs with the exception that baseline household size is replaced with baseline household size adult equivalent for the consumption runs. 18  Separate identification of lagged cumulative transfers from current transfers is possible because treatment households were randomly assigned benefits a year and a half before control households.

19
increasing tne value added content from these traditional commodities, or diversifying their agro-industrial export base.<sup>5</sup> 3. This absolute and relative decline of many African agricultural export sectors and the limited degree of export diversification in the region has led an increasing number of analysts tc conclude that the region's poor performance has less to do with adverse international market conditions than with internal institutional failures. Specifically, Africa's poor export and wider agricultural performance has been attributed to various forms of government or bureaucratic failure, including misguided macroeconomic and price policies, excessive government interventions in factor and commodity markets, and mismanaged and inefficient state-owned or state-directed marketing organizations.<sup>6</sup> Much of the recent social science research and literature on sub-Saharan Africa has been oriented toward documenting these and other dimensions of government failure.' 4. This analysis of misguided government policies and inefficient and inequitable institutional structures in African agriculture has led many researchers and donor agencies to Over the 1966-80 period, the total volume of African agricultural exports declined by 17 %, compared with a 23 % increase for all developing countries. (Calculated from FAO Trade Yearbooks) Significant export volume reductions occurred for Africa's three most important export crops--coffee. cocoa, and cotton. Over the 1970-85 period, SSA experienced a decline in its world market shares for nearly all of its most important export crops (Svedberg (1991, p.552). The region's exports of coffee, cocoa, cotton, tobacco, tea, and timber products have a far lower value added content than those for Latin America and Asia (World Bank (1981, Table 17).

6 This conclusion has been reached by analysts on different points of the political spectrum and for different ressons. Those sharing this conclusion include: Ellis (1982), Hart (1982), Hyden (1983, 1990), and Williams (1985) from the left of the political spectrum and Bates (1981), de Wilde (1984), and Berg (1985) from the right of the political spectrum.

7 Examples include: Arhin, Hesp, and van der Laan (1985), Cleaver (1986), Nellis (1986), FAO (1986), Ghai and Smith (1987) and World Bank (1981, 1989, 1990).

2
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|Regression Res|ults: Time invaria|ntPEP|
|---|---|---|
||Depe|ndent variable:|
|||cri|
||q)|(2)|
|PC supplier,time invariant|0.031°"*<br>(0.003)||
|PC buyer and supplier, time invariant||0.035"<br>(0.007)|
|Constant|0.632"**|0.632***|
||(0.055)|(0.055)|
|Observations|132,521|132,521|
|R2|0.451|0.451|
|Adjusted R2|0.450|0.450|
|Residual Std. Error (df= 132291)|0.195|0.195|
|FStatistic(df=229;132291)|475.408""*|474.689°**|

Note: “p<0.1; ““p<0.05; **“p<0.01 Included controls not shown are: Supl. location, Contract type, Year FE, Market FE, Contract value deciles