rafmacalaba/datause-encoder-data huggingface dataset:
|**No.**|**City**|**Population, urban area**|**Population, city**|
|---|---|---|---|
|14|Kanpur|3,132,844|2,823,249|
|15|Kochi|3,123,271|604,696|
|16|Thrissur|3,122,168|325,110|
|17|Indore|3,053,112|1,837,041|
|18|Nagpur|2,908,845|2,228,018|
|19|Coimbatore|2,814,268|959,823|
|20|Thiruvananthapuram|2,624,797|784,153|

_Source:_ UN World Urbanization Prospects 2018, https://population.un.org/wup/Download/Files/WUP2018-F12-Cities_Over_300K.xls.

# Appendix 5: Participants in focus group discussions and interviews

## Focus group discussions

### Profile of participants

Female and male owners of property were recruited to take part in focus group discussions (FGDs). Since the research aimed to understand the two groups’ differences in their choices concerning home ownership and recurrent property tax compliance, to ensure a meaningful comparison, the groups’ profiles were designed along the following minimum parameters.

#### _1. Property ownership_

- All participants should have a residential property in their name, either single ownership or joint ownership (with a member of the opposite gender).

- Wherever possible, each FGD group would have an equal mix of single and joint owners to facilitate understanding of decisions around joint and single ownership.

- For male joint property owners, the joint ownership should be with a female. This was to understand more clearly decisions on property purchase/ownership in light of gendered discounts and the influence of these discounts on having a female co-owner.

- For male property owners, the property purchase should have occurred after marriage. This was to understand more clearly the decision on property purchase/ownership in light of gendered discounts, since only male FGD participants who listed ownership jointly with their wives (in relevant cities) were eligible.

- Ownership of the property could not be acquired through inheritance, to ensure owners were liable for payment of stamp duty and property registration charges.

40
**Figure 13: Rising middle class as a share of population.**

<!-- Start of picture text --> Expansion of the middle class' size relative to the population<br>In percentage points over the 2005-2030 period<br>per<br>chl<br>ven<br>arg<br>cac<br>xlc<br>mex<br>bra<br>col<br>0 10 20 30 40<br>Base case projection Distribution-neutral projection<br>Difference Base case - Distribution-neutral expansion<br>per<br>chl<br>ven<br>arg<br>cac<br>xlc<br>mex<br>bra<br>col<br>0 2 4 6<br>Absolute difference<br><!-- End of picture text --> _Source:_ World Bank staff calculations.

Note: ARG-Argentina, BRA-Brazil, CAC-Central America & Caribbean, CHL-Chile, CHN-China, COL-Colombia, ECA-Europe & Central Asia, EUR-EU27 & EFTA, MEX-Mexico, MNA-Middle East & North Africa, PER-Peru, SAS-South Asia, SSA-Sub-Saharan Africa, USA-United States, XEA-Rest of East Asia, XHY-Rest of high-income, XLC-Rest of Latin America In Chile, Argentina and Colombia, growth of the middle class in the base case is greater than that simulated in the distribution-neutral scenario, indicating a progressive growth. Since growth in Chile benefits households at the lower tail of the distribution more than those at the upper tail, the middle class is expected to expand by four percentages points more than it would in a distribution-neutral growth scenario. On the contrary, the Brazilian growth is likely to widen income inequality.

Looking at the Growth Incidence Curve (GIC) confirms the previous remarks and shows a great variation in the distributional effect of economic growth across countries in LAC. The GIC 29
# **1 Introduction**

Cross-border mergers and acquisitions (M&A) have been among the most striking international economic phenomena of the last two decades. While the determinants of M&A have been studied at the aggregate level, there is little analysis of the determinants of M&A in services sectors. This is surprising, given that these sectors accounted for 65 percent of global cross-border M&A deals in the period 1990-2012 (UNCTAD, 2013). This paper presents evidence on the determinants of the M&A in services seen through the lens of a model featuring a role for both policy and inter-sectoral linkages. The empirical analysis is based on a large sample of developed and developing economies, and a new database on services policy measures.

We proceed in three steps. First, we present some broad patterns emerging from our data. Aggregating our transaction-level M&A data into a country-level and bilateral database, we show that the fraction of country-pairs with non-zero M&A flows is small. We also present cross-country evidence on policy restrictiveness in trade in services drawing on a new policy database. Detailed information on restrictions on the forms of entry, licensing, operations and regulation are aggregated into a Service Trade Restrictiveness Index (STRI), computed for five service sectors in each of 103 countries. The country-level STRI is broadly declining in the GDP per capita, i.e. developing countries tend to have more restrictive policies than developed countries. Restrictiveness in sectors such as transport and legal services seems to be much higher than for other services in all countries, irrespective of their level of development.

Second, we propose a stylized model of M&A featuring heterogeneous firms and a role for inter-sectoral linkages. The manufacturing sector is perfectly competitive, and it produces a homogenous good using labor and intermediate services. This assumption reflects evidence from the OECD STAN Input-Output tables that services are important intermediate inputs in the production of manufacturing across a wide range of countries. In our model, services are characterized by product differentiation and they are produced by heterogeneous firms under monopolistic competition. M&As in services are presented as a way of serving foreign 2
<!-- Start of picture text --> Qatar: Real Credit<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term cycle Real credit growth (y/y)<br>60<br>40<br>20<br>0<br>-20<br><!-- End of picture text -->

# **B- Oil importers**

<!-- Start of picture text --> Jordon: Real Credit Morocco: Real Credit<br>(in percent) (in percent)<br>1967 1977 1987 1997 2007 2017<br>year 1967 1977 1987 1997 2007 2017<br> Medium-term cycle Real credit growth (y/y) year<br> Medium-term cycle Real credit growth (y/y)<br>Lebanon: Real Credit Tunisia: Real Credit<br>(in percent) (in percent)<br>1967 1977 1987 1997 2007 2017 1967 1977 1987 1997 2007 2017<br>year year<br> Medium-term cycle Real credit growth (y/y) Medium-term cycle Real credit growth (y/y)<br>West Bank and Gaza: Real Credit Yemen: Real Credit<br>(in percent) (in percent)<br>1967 1977 1987 1997 2007 2017<br>year 1967 1977 1987 1997 2007 2017<br>year<br> Medium-term cycle Real credit growth (y/y)<br> Medium-term cycle Real credit growth (y/y)<br>60<br>60<br>40 40<br>20 20<br>0<br>0<br>-20<br>-20<br>60<br>30<br>40 20<br>20 10<br>0 0<br>-20 -10<br>-40 -20<br>30<br>40<br>20<br>20<br>10<br>0 0<br>-10 -20<br>-20<br>-40<br><!-- End of picture text --> 35
level of statistical significance.<sup>21</sup> In columns (5) to (8), we present an alternative specification that controls for survey fixed effects (which are country-year specific) rather than country and year fixed effects. These within survey estimates in essence remove country level omitted variable bias from both time-varying and time-invariant covariates. The qualitative results in columns (1) to (4), in terms of sign as well as relative magnitude between MSMEs, SMEs and large firms, carry through in these specifications.

As robustness, in appendix A3 we estimate columns (1) to (4) from Table 3 over the Orbis sample and obtain qualitatively identical results.<sup>22</sup> In all regressions in this table, we use OLS regressions with firm and year fixed effects with standard errors clustered at the firm-level. Overall, firms with access to a loan have an average annual employment growth rate that is 1 percentage point larger than that for firms that lack such financing in the Orbis sample. As before, we find the association to be strongest in the case of MSMEs with a point estimates more than four times higher than that of large firms. We confirm with a t-test that it is statistically higher at the 99% confidence level.

In columns (5) to (12), as robustness, we present results using two additional measures for the volume of financing – growth of finance and debt ratio. In columns (5) to (8), we find that a 1 standard deviation increase in the growth of finance correlates to an overall increase in employment growth by 0.81 percentage points. This relationship appears entirely driven by the high correlation among MSME firms. A 1 standard deviation increase in the growth of finance is associated an increase in employment growth by 0.89 percentage points among MSMEs and only

> 21 Micro firms with access to a loan increase employment growth at a rate of almost 5 percentage points larger than that of micro firms without a loan, by far the sub-sample with the highest correlation. 22 All analysis using ORBIS data is done using the full sample of firms available even when data for a particular firm is not available for all years. As robustness check, we repeated all our analysis over a balanced panel that drops firms not available over the entire 2004-2011 timeframe. Although the number of countries and the sample size drops substantially, all results carry through. The regression tables are available on request.

20
- Porter, R. (1983), "A Study of Cartel Stability: The Joint Executive Committee, 18801886," _Bell Journal of Economics,_ 14:2:301-314.

- Revenga, A. 1994. "Employment and Wage Effects of Trade Liberalization: The Case of Mexican Manufacturing." Mimeo. The World Bank.

- Robbins, D. J. 1996. "Evidence on Trade and Wages in the Developing World." OECD Development Centre Technical Papers No. 119. Paris: OECD.

- Roberts, M. J. and Tybout, J. R. 1996. Industrial Evolution in Developing Countries: Micro Patterns of Turnover. Productivity, and Market Structure. New York, NY: Oxford University Press.

- Roberts, M J. and Skoufias, E. 1997. "The Long-Run Demand for Skilled and Unskilled Labor in Colombian Manufacturing Industries." Review of Economics and Statistics 79: 330-334.

- Rodrik, D. 1997. Has Globalization Gone Too Far? Washington, DC: Institute for International Economics.

- Sevestre P. and A. Trognon (1996), "Dynamic Linear Models" in Matyas, L. and P Sevestre. The Econometrics of Panel Data, (Boston: Kluwer Academic Publishers),100-1 18.

- Slaughter, M. J. 1997. "International Trade and Labor-Demand Elasticities." NBER Working Paper 6262.

- Sosin, K. and Fairchild, L. 1984. "Nonhomotheticity and Technological Bias in Production." Review of Economics and Statistics 66: 44-50.

- Wood, A. 1994. North-South Trade. Employment, and Inequality: Changing Fortunes in a Skill-Driven World. Oxford: Clarendon Press.

- Wood, A. 1995. "How Trade Hurt Unskilled Workers." Journal of Economic Perspectives 9(3): 57-80.

- Wood, A. 1997. "Openness and Wage Inequality in Developing Countries: The Latin American Challenge to East Asian Conventional Wisdom." The World Bank Economic Review 11(1): 33-58.

26
30 work where a research tradition has already developed (the paradigm is set), where methodological issues are relatively well-drawn (though breakthroughs may be needed, the need itself is implicitly recognized) and where data are already available or the mechanisms for collecting data are well known. (For example, for work on the determinants of health, the mechanisms for collecting representative household data for analysis of household behavior in such areas as health have been the subject of considerable effort in the last two decades). None of these factors obtains today.

Consequences of poor health for households and communities. The third approach would be greater attention to the consequences of poor health for households and communities. This might be considered a sensible partial approach, concentrating on individual and community costs, to the larger challenge of cost-benefit analysis. Though little such work has been completed, World Bank staff are currently exploring the possibility of undertaking research along these lines, concentrating on the consequences of adult ill health. The feasibility of more general work on adult health issues (including measurement of adult mortality, and study of the determinants of adult health) is also being explored; any work on adult health would be likely to increase our understanding of the consequences of poor health for the development process.<sup>38</sup> 38 Regarding the World Bank's recent efforts, see Over et. al. (1989), and Feachem (1989). The World Bank has also recently completed two country studies, of Brazil and China, each with a heavy concentration on issues of adult health; see World Bank (1989a and 1989b).
countries in the 1990s. About $167 billion in private capital flows to these countries were recorded in 1995 accounting for three-fourths of the total net aggregate long-term resource flows to developing countries that year, up from 44 percent in 1990. This is mainly attributed to the spectacular rise in portfolio flows (in the form of bonds and equities) and strong growth in foreign direct investment (FDI).<sup>3</sup>

**Figure 1**

# **Aggregate net resource flows to developing countries, 1986-95**

<!-- Start of picture text --> US$ billions<br>250<br>Portfolio equity investment<br>200 Foreign direct investment . .<br>Net private debt flows . ,.<br>- Net official Loans<br>150 E Official Grants<br>100<br>50<br>o _<br>1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 e<br><!-- End of picture text --> e = Ertimated. Source: World Bank, Debtor Reporting System (DRS).

This episode is different from the past in that not only has the magnitude of private capital flows to developing countries in the 1990s been significantly larger than the 1970s, the investor base and range of instruments of private flows are wider now. The recipients of capital flows within developing countries are also changing. Unlike the late 1970s, when private capital to developing countries flowed mainly to sovereign and parastatal 3 Ibid.

4
vulnerable to floods across in all four agricultural seasons compared to the rest of the farmland size groups. The average farm size in Zambia was between 4 and 5 ha across the three survey waves (Table 2). Households owning 5-10 ha, a relatively small group, are generally comprised of emergent farmers. The bivariate results in Table 2 do not show a clear difference in exposure to self-reported climate risks by poverty status.

Table 2: Proportion of Zambian households that experienced floods and/or droughts in any part of their fields by season, gender, farm size, and Province.

||**2015/201**|**6 season**|**2016/2**|**017 season**|**2017/20**|**18 season**|**2018/20**|**19 season**||
|---|---|---|---|---|---|---|---|---|---|
||**Floods**|**Droughts**|**Floods**|**Droughts**|**Floods**|**Droughts**|**Floods**|**Droughts**|**n**|
|**All households**|9.6|12.7|11.2|17.2|12.3|39.7|12.03|63 .4|7,240|
|**Female headed**|8.14|11.4|10.7|16|13.7|37.4|11.3|63.3|1729|
|**Male headed**|10.2|13.2|11.4|17.7|11.8|40.6|12.3|63.4|5511|
|**Poor**|9.63|12.34|11.45|16.82|12.11|41.30|11.81|65.46|6530|
|**Farm size**||||||||||
|**0-2 ha**|7.15|14.0|9.28|17.9|10.7|40.8|13.0|60.1|3283|
|**2-5ha**|11.7|12.4|12.4|18.1|12.4|42.0|13.2|62.1|2712|
|**5-10ha**|10.5|11.4|12.4|15.6|14.3|36.2|9.33|68.1|861|
|**>10ha**|11.5|9.43|14.0|10.6|18.0|27.0|4.89|80.6|384|
|**Net Income**||||||||||
|**25**<sup>**th**</sup>**Percentile**|7.49|13.6|8.78|19.4|11.6|43.7|14.2|63|1810|
|**50**<sup>**th**</sup>**Percentile**|10.6|14.2|12.9|19.1|13.7|40.6|13.5|63.5|1810|
|**75**<sup>**th**</sup>**Percentile**|10.9|10.6|12.4|15.5|13.2|36.1|9.68|61.4|1810|
|**Gendered househo**|**ld type**|||||||||
|**Female adults**|7.54|11.6|8.85|15.8|13.4|36.3|11.0|63.9|821|
|**Male adults**|8.09|11.1|9.39|16.5|13.3|37.7|10.4|64.1|366|
|**Male and**<br>**Female adults**|10.1|13.1|11.7|17.5|12.1|40.4|12.3|63.2|6048|
|**Children**|0|0|0|0|0|78.0|0|83.4|5|
|**Province**||||||||||
|**Central**|12.9|4.92|15.2|8.21|10|50|5.24|77.2|566|
|**Copperbelt**|3.3|16.5|2.53|22|1.93|52.7|1.64|68.3|502|
|**Eastern**|7.06|23.9|9.37|34.4|9.65|66.8|33.1|46.1|1917|
|**Luapula**|3.37|7.31|5.98|8.62|8.49|20|5.48|40.2|615|
|**Lusaka**|5.99|6.08|10.6|6.54|6.67|26.6|2.31|85.2|404|
|**Muchinga**|6.08|12.3|8.18|16.2|12.9|33.3|21.2|33.8|679|
|**Northern**|6.54|21|5.72|30.3|13.1|35.8|17.3|43.7|707|
|**North-Western**|3.68|1.58|7.47|3.91|7.82|14.7|4.69|57.2|486|
|**Southern**|16.1|10.3|11.9|11.3|7.82|41.8|0.33|99|810|
|**Western**|22.6|8.68|30.6|8.37|39.2|19.9|3.51|95.1|554|

Source: Own calculations from RALS (2019).

Figures S8 and S9 show the spatial distribution of floods and droughts over the past four agricultural seasons at the province level. As expected, a larger proportion of households 13
# **The Remitting Patterns of African Migrants in the OECD**<sup>**#**</sup>

Albert Bollard, _Stanford University_ David McKenzie, _World Bank_ Melanie Morten, _Yale University_ _Keywords:_ Remittances, Migration, Africa. _JEL Codes:_ O15, F22, J61.

> # We are grateful for funding for this project from the Agence Française de Développement (AFD) and the World Bank’s Africa Migration Project. We thank the various individuals and organizations who graciously allowed us to use their surveys of immigrants and Hillel Rapoport for his collaboration on the broader project. All opinions are of course our own and do not represent those of AFD, or of the World Bank.
- 5 -

annuities. The increase in the number of annuity providers in the 1990s led to a continuous decrease in concentration ratios. In recent years some life insurance companies have decided to exit the annuities segment of the life insurance market, discouraged by the intensive competition, the thin intermediation spreads and the relatively low returns on equity. These factors have resulted in an increase in concentration ratios, but the annuities sector in Chile remains more competitive than the AFP sector, whether measured by the number of participants or concentration ratios.

<!-- Start of picture text --> Figure 1<br>Market Concentration Ratios in Pensions and Annuities<br>Herfindahl and Share of Three Largest Firms, 1988-04<br>2500 100%<br>90%<br>2000 80%<br>70%<br>1500 60%<br>50%<br>1000 40%<br>30%<br>500 20%<br>10%<br>0 0%<br>1988 1990 1992 1994 1996 1998 2000 2002 2004<br>AFP Herfindahl Annuity Herfindahl<br>AFP 3 Larges t Annuity 3 Larges t<br>Source : SVS, SAFP<br>Herfindahl Ratio Share of 3 Largest<br><!-- End of picture text --> The performance of the annuities market can be measured by the relationship between the annuity rate (defined as the internal rate of return on the annuity) and the risk free rate. As shown in Figure 2, the average annuity rate reported by life insurance companies tracked the interest rate on 20 year Central Bank bonds reasonably well during the 1990s.<sup>3</sup> In the early 2000s the difference between the two rates inverted, and the annuity rate has exceeded the risk-free rate since that point. This negative difference between the risk-free rate and the annuity rate is unusual. For example, Brown et al (2001) calculate the internal rates of return on US annuities and obtain rates ranging from 5.9 to 6.5 percent p.a., lower than the yields of 10 and 30-year Treasury bonds, which were 7.1 and 7.3 percent p.a. in the same period. James, Song and Vittas (2003) perform the same exercise for several countries and obtain similar results.

This inverted differential implies a good deal for annuitants but raises the question of whether providers have generated losses on their annuity business. Annuity providers can in principle pay higher annuity rates and still achieve positive spreads by investing in higher yield paper, and Table 2 indicates that the industry has shifted towards higher yield mortgage-related securities and corporate bonds since 1995. The move towards corporate bonds since 2000 is particularly noteworthy, with the share of this instrument increasing from 10 to almost 35 percent of the portfolio. These instruments are also indexed to prices and pay a higher yield than Government and Central Bank bonds, allowing providers to

> 3 Until 2005 insurance companies had to calculate and disclose their annuity rates using the RV-85 mortality table.  Since 2005 annuity rates have been calculated and reported with an updated mortality table, the RV04.  The adoption of the RV-04 leads to higher annuity rates, with the difference amounting on average to about 50 basis points.  For a more detailed discussion on the various mortality tables in Chile see Rocha and Thorburn (2006).
- 83 -

- requested, as compared with 354 for Brazil and 571 for the USA (Kravis, Heston and Summers, 1982, p. 45).

- 2) Although our "price" information is implicit, the unit values we derive refer to actual transactions, and they cover all such transactions throughout the year and for all parts of the country. Specification prices, by contrast, are quotes, shelf, list or monitored market prices for one point in the year in a limited number of locations. For example, for Mexico, in order "to obtain national average prices it was necessary to obtain an average of the various urban prices and to take account of rural prices. The adjustment for rural prices was done roughly on the basis of a sample survey of forty common items in rural areas linked to several of the major provincial cities. From these rural and urban prices, adjustment factors were obtained to move from urban to national average prices" (Kravis, Heston and Summers, 1982, p. 43). Quite clearly, the ICP pricing technique involves an elaborate process of collection, adjustment, and data merge, and what comes out of in the wash is not always as clean as was specified.

# Conclusion

The industry of origin and the expenditure approaches are complementary techniques. Each approach had its weaknesses and its strengths. A detailed reconciliation is not feasible by comparison of unit values and specification prices because the one approach deals with producer prices and the other with final expenditure. The nature of the reconciliation problem also depends on whether the basic comparisons are of a binary kind, such as we have attempted here and which was also the case in the early expenditure comparisons of OEEC; or multilateral, as was the case in ICP III, and in the recent studies of EUROSTAT and OECD. In multilateral studies where "international" prices are used, the problem of representativity becomes much more complex, as items have to be selected which are "representative" across a very wide range of countries (see Krijnse Locker, 1984; Ghosh, 1984; and our remark above relating to motor vehicles).