rafmacalaba/datause-encoder-data huggingface dataset:
# **Online Appendix: Not for Publication**

Table A1: Education and Cognition Interaction

||**Ru**|**ral**|**Ur**|**ban**|
|---|---|---|---|---|
|Father Edu|0.333***|0.226***|0.408***|0.278**|
||(0.021)|(0.071)|(0.027)|(0.121)|
|Ability Index|0.524***|0.702***|0.333***|0.420*|
||(0.055)|(0.109)|(0.066)|(0.225)|
|Ability Index Sq|-0.029***|-0.046***|-0.007|-0.015|
||(0.004)|(0.010)|(0.006)|(0.022)|
|Father Edu_×_Ability Index|0.004|-0.044|-0.002|-0.003|
||(0.003)|(0.030)|(0.004)|(0.055)|
|Father Edu Sq||0.013**||0.011|
|||(0.006)||(0.007)|
|Father Edu_×_Ability Index Sq||0.005*||0.000|
|||(0.003)||(0.005)|
|Father Edu Sq_×_Ability Index||0.002||-0.001|
|||(0.002)||(0.003)|
|Father Edu Sq_×_Ability Index Sq||-0.000||0.000|
|||(0.000)||(0.000)|
|Constant|5.432***|5.510***|5.673***|5.889***|
||(0.201)|(0.282)|(0.237)|(0.490)|
|Observations|10239|10239|5238|5238|

Notes: Standard errors are clustered at the community level (*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1). Rural and Urban are defined based on location of birth. If the respondent was born in a big city or town, it was considered as Urban, and if the respondent was born in a village, it was considered Rural. Cognitive ability index is expressed in percentile; it is constructed taking the first principal component of Raven Test and two memory memory tests net of age and age square.

1
This section investigates in detail what channels job gains could propagate from manufacturing to the service sectors. Identifying the exact mechanism would provide useful information for economists and policy makers to understand the full employment equilibrium effects of new export opportunities in developing countries.

We examine three potentially important channels. The first channel operates via demanddriven propagation. That is, newly employed manufacturing workers could increase spending on local services, such as wholesale, retail and restaurants, generating new jobs in local commerce. The second channel operates via production linkages, that is, via higher demand for inputs from manufacturing production. Expanding production activities of the manufacturing sector could require more input from local supporting service industries, such as accounting, tax and other consulting, architecture, advertising, protection, housecleaning or packaging. This would help create more jobs in the supporting service sectors. The third channel operates via increasing real estate and construction activities, benefiting from, for example, a house price appreciation.

We examine these channels by dissecting to the finest sectors possible (which is at twodigit) and combining this with information about households’ expenditures. We focus on sectors that best reflect the channels we are discussing. Specifically, we focus on (i) sales of vehicles and vehicle parts, (ii) wholesale, (iii) retail and (iv) hotels and restaurants to examine the demand channel. This is because they are more likely to reflect final consumption (i.e. consumption from households). To examine the production channel, we focus on supporting industries (code 74 in Table A1 of the Appendix). Ideally, one would use the input-output table to examine production linkages. However, since employment data are only available at the two-digit level, we examine the impact on the aggregate supporting industries. Finally, we focus on real estate and construction employment to examine the real estate channel.

26
21 less in the terms of trade counterfactual.12 This happened because the industrial trade prices dropped sharply in the early 1980s, pushing actual real rates to 20 percent or more.

Another counterfactual scenario, in which all countries who paid their interest do better, starts with the actual debt at the end of 1980 and assumes the constant 4 percent re.l rate from 1981 through 1986. We can think of this as the soft-landing counterfactual -- Paul Volcker stops inflation but restarts money growth in time to keep real interest rates from going up high as they did. The right-hand parts of Tables 6A, B and C show that by 1986 the accumulated impact high interest rates since 1980 had lowered net worth of HICs and LAC countries by about 152. For other groups the impact was smaller. We can also evaluate this gain by asking how much lower would their debt be if countries had not borrowed to pay higher interest rates associated with the hard landing. Venezuela, Ecuador, Yugoslavia, and Mexico were hardest hit; real rates above 42 in the 1980s accounted to over 30 percent of their debt by 1986. Other major Latin debtors would have had 20-30 percent less debt with the soft landing.

Anecdotal evidence suggests that if real interest rates had not sunk so abnormally low in the late seventies countries would nit have borrowed as heavily, but modelling prudence in primary borrowing as a function of the current real interest rate lies beyond the scope of the paper. It might be difficult to construct a plausible model of rational decision making that would replicate the borrowing patterns of the 1970s and early 1980s.

12 These trade prices are the average of the dollar unit value of exports and dollar unit value of imports for industrial countries, as reported in the IMF, IFS.
# _Per Capita Sales Taxes (ISS)_

Municipalities are required by federal law to have a sales tax. The sales tax collected per capita is another indicator of commercial firms’ willingness to fund the local government. The sales tax rate varies across municipalities and can be set between 2% and 5%. Complete data on municipal sales tax rates are not available, but we account for this variation in a sub-sample of the 100 most populous municipalities in São Paulo below. We use the base 10 logarithm of this indicator as well. The mean is 2.65 and the standard deviation is 1.36.

# **Independent Variables**

# _Voluntarily‐adopted Policy Management Councils_

We use the Brazilian Institute of Geography and Statistics’ survey data on the presence of 21 different local policy councils among Brazil’s municipalities (IBGE 2016). These councils include health councils, women’s councils, housing councils, and cultural councils among others. Municipalities adopt some councils, such as health and education councils, at very high rates due to federal financial incentives. For example, the mean health council adoption rate in our data is 80% and adoption rates in 2013 approach 100%. Thus, the presence of a health council is an inappropriate measure for testing our arguments connecting participatory institutions to tax outcomes due to the very low variation across municipalities. However, many other councils could relate to public services, democratic accountability <mark>, legitimacy, and taxation and carry no federal funding with them. For example, urban planning, food security, environmental sanitation, and women’s rights councils do not come with federal funds. The adoption rates for these councils are subsequently much lower, as low as 5% across Brazil.</mark> We treat the councils that carry no federal funding as being more “voluntary” than those for which there is a clear financial benefit for municipal adoption. The presence of voluntary councils allows for a better test of our arguments than the “induced” councils because their adoption is not required. We thus hypothesize that adopting these more voluntary councils represents a greater municipal and civil society commitment to democratic participation than does adopting councils with federal inducements. This argument is consistent with scholarship connecting the growth of a stronger civil society and an interested mayoral administration with the voluntary adoption of additional councils (Pires and Vaz 2012; Gurza Lavalle et al. 2015). Finally, voluntary council adoption signals that CSOs and public officials also seek collaborative relationships to improve policy outputs.

We use several variables to account for the presence of local policy councils. First, we use a dummy variable to record whether municipalities have a council presence that is greater or lesser than the mean. This indicator is coded “1” if a municipality features 16
in the sample worked 34.2 hours per week (i.e., including zeros) and this number rises to 44.8 for those who worked a positive number of hours. Lastly, the average monthly labor income for mothers with at least two children is 50,166 old leks (221,591 without zeros), whereas fathers earn on average 191,841 old leks (331,172 without zeros), which is quite more compared to mothers.<sup>14</sup> Once again, it is important to notice the gender inequality in terms of labor-force participation and earnings in Albania during the period analyzed in this study.

# **5 Empirical Strategy: Instrumental Variables**

## **5.1 Son Preference in Albania and Siblings Sex-Composition**

In this context, I exploit Albanian parental preference for having sons combined with the siblings sex-composition as an exogenous source of variation in the fertility decision. For this empirical strategy to identify the parameter of interest, the instrument sibling sex-composition must satisfy two basic conditions: (i) must be strongly correlated to the fertility choice and (ii) it must have no correlation with factors directly affecting parental labor-force participation other than through its impact on fertility.

Several demographic analyses have confirmed that son preference is a distinctive feature of Albania’s population (UNFPA, 2012; Gjon ̧ca, Aassve and Mencarini, 2008). It is well documented that if the first child of an Albanian couple is a daughter, they will try to have at least one more child (Zickel and Iwaskiw, 1994). Son preference in Albania is partially driven by the desire and need to perpetuate the family name, but is also reinforced by a collection of customs that make a son desirable economically. For instance, Albanian sons are considered more economically productive than daughters not only because they obtain higher wages, but also because they tend to remain part of the extended family, while daughters and their contribution to the family where they are born counts only for a few years.

Old-age support from mature sons is another influential factor in parental decisions to have sons in Albania. They are still more preferred than daughters because they provide a greater source of protection and expected support for the parents at old age, a need reinforced by the uncertainties of the economic and social environment since the exit from the communist regime. Moreover, Albanian tradition and culture dictates that sons should provide financial support and protection for parents. In particular, Albanian custom obliges the youngest son (and his wife) to take care of his parents in their old age - indeed the youngest son is referred to in Albania as “the son of old age” (King and Vullnetari, 2006; King, Mata-Codesal and Vullnetari, 2013).

On the contrary, the obligation of daughters is much weaker, in part because they are considered as transient members of their native family and also because they are thought to be

> 14Monthly labor income is in real terms with base year 2007 using the national CPI provided by the Albanian National Institute of Statistics (INSTAT).

12
reference cluster. The variables and their sources are described in Appendix 2. The regressors fall into three broad categories:

**Figure 2: Correlations between Growth and the Sources of Vulnerability**

<!-- Start of picture text --> Private Sector Credit Growth (%) Fiscal Deficit (% of GDP)<br>150 20<br>100 10<br>50 0<br>0 -10<br>-50 -20<br>-10 0 10 20 30 -10 0 10 20 30<br>Loan-to-Deposit Ratio (%) REER Overvaluation<br>600 .2<br>400 0<br>200 -.2<br>0 -.4<br>-10 0 10 20 30 -10 0 10 20 30<br>External Debt (% of GDP) Short-term Debt (% of Foreign Reserves)<br>150<br>600<br>100<br>400<br>50 200<br>0 0<br>-10 0 10 20 30 -10 0 10 20 30<br>Real GDP Growth (%)<br>Cluster L Cluster V Cluster G Cluster H<br><!-- End of picture text --> Sources: IMF’s World Economic Outlook database and authors’ calculations.

Notes: The lower growth and lower vulnerability is identified by L, the lower growth and higher vulnerability is identified by V, the higher growth and lower vulnerability is identified by G, and the higher growth and higher vulnerability is identified by H. The absence of higher growth, higher vulnerability data in 2000 and 2008 reflects the lack of countries in such cluster.

- <u>Initial conditions. These comprise measures that may be susceptible to policies and institutional</u> changes over a relatively long period. This category includes measures that reflect a country’s economic development and its economic structure, as well as the degree to which an economy is open to the flows of goods and capital. This includes the initial level of income and oil trade balance as a share of total exports plus imports. In addition, measures of trade (exports and imports as a percentage of GDP) and financial (FX assets plus liabilities as a percentage of GDP) openness are included and, in turn, these are accompanied by indicators that serve to qualify the type of openness experienced by individual countries. Specifically, the difference between export and import growth rates is used to assess the type of trade openness. Also, FDI (net, as a percent of

7
**Table 10. Odds ratios from logit model of growth, by wave, ELMPS 1998-2018**

|||**Pool with**<br>**subsequent**||
|---|---|---|---|
||**Pool**|**formality**|**2012-2018**|
|**Base wave formality (informal omit.)**||||
|Formal|1.096|1.233|0.729|
||(0.339)|(0.414)|(0.243)|
|**Subsequent wave formality (informal omit.)**||||
|Formal||1.287||
|||(0.412)||
|**Wave (1998-2006 omit.)**||||
|06-12|0.371***|0.341***||
||(0.105)|(0.106)||
|12-18|0.560*|0.503*||
||(0.162)|(0.166)||
|**Interactions between base formality and wave**||||
|06-12|1.056|0.713||
||(0.407)|(0.329)||
|12-18|0.897|0.779||
||(0.337)|(0.332)||
|**Interactions between subsequent formality and wave**||||
|06-12||1.660||
|||(0.760)||
|12-18||1.350||
|||(0.580)||
|**Ent. size (one worker omit.)**||||
|2|0.308***|0.319***|0.332**|
||(0.073)|(0.076)|(0.142)|
|3-4|0.188***|0.174***|0.236*|

67
# FIGURE E.8

LABOR INTENSIVE NET EXPORTS 1988 <!-- Start of picture text --> 3<br>1W<br>2<br>lr<br>w<br>N 1<br>0<br>2_ m PA<br>,,, 3 CA<br>2 -<br>w -2<br>w<br>z<br>-3<br>-4<br>0 10 20 30 40 50 60<br>CAPITAL PER WORKER (1000 US$)<br><!-- End of picture text -->
Harrington‟s _The Other America_ in the _Viewer_ skyrocketed from the early 1960s, peaking around 1970, and falling steadily since. (The graph can be found here.) Notice that there is a pronounced “bubble” in references to poverty, peaking around 1970 (Figure 1). Consistently with this first factor, I conjecture that this bubble reflects the shock of re-discovering poverty in America. The success of Harrington‟s book was a surprise at the time; the first print-run was 2,500 copies, but by the mid-1990s it had sold 1.3 million copies. In due course, the trajectory returned to normal. Of course, if one “smoothes out” this bubble sufficiently, then one sees a clear upward trend in references to poverty starting around 1950 through the end of the century, as can be seen here (using a smoothing parameter of 20 years).

The influence of these writings depended, of course, on their historical context. Harrington and Galbraith clearly wrote their books at the right time to have the influence they had, given the combination of new affluence (for the majority) and optimism (including about policy) that prevailed in America in the 1950s and „60s. But as times changed, a backlash emerged, as has often happened. The counter-attack came in the 1980s; Charles Murray‟s (1984) _Losing Ground_ was an example in the written record. Welfare reforms followed in the US in the 1990s—reforms that were contentious among poverty scholars and advocates in the US. 30 years after declaring a “War on Poverty,” America declared a “War on Welfare.”<sup>7</sup> There are continuing debates today about poverty—its causes and the appropriate policy responses, throughout the world.

The second factor in the surge of attention to poverty in the late 20th century was the public‟s increasing awareness of the existence of severe and widespread poverty in the developing world. Poverty in developing countries started to attract mainstream scholarly attention in the 1970s.<sup>8</sup> The World Bank‟s (1990) _World Development Report: Poverty_ was influential in development policy circles, and soon after a “world free of poverty” became the Bank‟s overarching goal. A large body of empirical research on poverty followed in the 1990s. The UNDP‟s _Human Development Reports_ began in 1990, and have argued for public action to promote basic health and education in developing countries.

> 7 The latter term was used by Katz (1987); also see Albelda et al. (1996).

> 8 Important contributions in the period 1970s and‟80s included Dandekar and Rath (1971), Adelman and Morris (1973), Chenery et al. (1974), Lipton (1976), Fields (1980), Kakwani (1980), Sen (1981), Anand (1983), Bardhan (1984) and Kanbur (1987).

8
|The Banker Database|The Financial Times|Firms in the financial sector in more than<br>190 countries covering 5,000+ public,<br>private, government and subsidiary banks<br>accounting for more than 90% of total global<br>bankingassets|Yes|No|
|---|---|---|---|---|
|Fitch Connect|Fitch Solutions|Financial data on 36,000+ banks, 12,000+<br>insurers, 117 sovereigns, and 3,000+<br>corporates globally across developed and<br>emergingmarkets.|Yes|No|
||IJGlobal (part of the<br>Euromoney<br>Institutional Investor<br>PLCgroup)|Firms in the global infrastructure finance<br>sector, including 636 SOEs globally|||
|Uniworld online|Uniworld|Firms with headquarters in over 200<br>countries and 20,000 industries|Yes (revenue,<br>employees)|No|
|Bloomberg|Bloomberg Finance<br>L.P.|Data for more than 5 million legal entities,<br>including public & private companies,<br>sovereign entities, funds, governments,<br>agencies, and municipalities|Yes|Yes|
|Banker's Almanac|LexisNexis Risk<br>Solutions|Firms in the financial sector covering<br>200,000 financial institutionsglobally|Yes|Yes|
|CB Insights|CB Insights|Global database on private firms and<br>investor activities.|Yes|Yes (investment and acquisition<br>data only)|
|S&P Capital IQ|S&P Global Inc.|Data on more than 62,000 public firms and<br>18.2 millionprivate firmsglobally.|Yes|Yes|
|Extractive Industries<br>Transparency Initiative<br>(EITI)|EITI|Firms in the extractive industries sector,<br>covering 60 SOEs in 20 EITI countries|No (revenue data<br>at the mining<br>project level)|<br>Yes (tagged as SOE)|

Source: Authors’ elaboration 41
_Potential problems associated with free_ **_entry_** _Section 4_ decision is proximity, so location is key to market share, and thus to revenue and profits.

This outcome has occurred in some cases where there has been free entry in urban bus industries. Scheduling is a problem because waiting time is so dominant in passengers' travel decisions that customers will almost always take the first bus that comes. This leads to ongoing revisions of schedules as each bus company seeks to schedule its services just ahead of the competitors' services. Furthermore, it means there is little incentive to compete strongly on price or quality.

For example, problems emerged following the deregulation of urban buses in Britain during the 1980s. All urban bus services (except in London) were deregulated and privatised. Where competition occurred entrants competed by scheduling services along the same routes for very similar fares. Destructive competition emerged as routes were swamped by incumbents responding by trying to schedule services so frequently that entrants could not get enough passengers to be viable<sup>5 8</sup> Scheduling problems such as this are most likely to occur where the demand decision is dominated by timing considerations and there is:

- a homogeneous product with little value attached to brand;

- low sunk costs; and

- low costs of changing timetables.

A market solution could exist to these problems. If competition over routes and schedules is unsustainable, one could assume that the competing firms would have an incentive to define geographical monopolies. However, the question remains whether: * transaction costs and competition law would allow such a market solution to occur;

- the solution would be sustainable since new companies which were not part of the original agreement could always enter an established company's area; and

- the process of arriving at the market solution, and indeed the equilibrium outcome, would be less costly to society than restrictions on entry and competitive award of monopoly franchises.

In industries such as urban transport, the typical regulatory response has been franchising of monopoly rights to groups of routes. Where there are low sunk costs, frequent tendering for monopoly franchises may offer a good solution. While it prevents free entry for the period of the franchise, it offers regular opportunities to

- _58_ Klein, Daniel and Moore, Adrian, _Schedule jockeying and route swamping:_ **_bus_** _markets in Britain need kerb rights_ Institute of Economic Affairs (June 1997).

_52_
**Figure 5: Relationship between housing prices and public accessibility* by quartiles of informality****

<!-- Start of picture text --> Price and public accessibility by level of informality- 2009 Price and public accessibility by level of informality- 2013<br>2<br>1<br>1<br>2<br>3<br>4<br>3 4<br>1000 1500 2000 2500 3000 3500 1000 1200 1400 1600<br>Distance to Metro station Distance to Metro station<br>1400000 2000000<br>1300000<br>1500000<br>1200000<br>Median Price Median Price<br>1100000<br>1000000<br>1000000<br>900000 500000<br><!-- End of picture text --> Notes: *Public Accessibility measured by distance to the Metro station. **Informality measured by the proportion of informal workers in the living in the neighborhood, neighborhoods in quarter four has the greatest proportion of informal workers.

Figure 5 suggests that households located in neighborhoods with the greatest levels of informality are further away from Metro stations and have lower housing prices than households located in neighborhoods with lower level of informality. The spatial segregation we identified when we split the sample by education status is also observed when we categorize observations by level of informality. Households located in low-educated neighborhoods, as well as households located in high-informal neighborhoods are not well located, both in terms of proximity to employment subcenters, and in terms of distance to the Metro station.

From these descriptive statistics, we can anticipate two conclusions from the analysis: (i) first, in terms of housing prices, households located in high-educated neighborhoods and in neighborhoods with low level of informality face greater housing prices than households located in low-educated or highly-informal neighborhoods. These results are evidence of the existence of economic segregation in the city; (ii) second, high-educated households and households located in neighborhoods with low levels of informality are better located: both in terms of access to employment subcenters, and proximity to public transport infrastructure. Hence, on top of the economic segregation, spatial segregation and a reduction of opportunities for lower income households are observed in Mexico City.

18