rafmacalaba/datause-encoder-data huggingface dataset:
exposure to natural calamities, are given only for two years (1998/99 and 2010/11) as these variables were not available in the 1991/92 survey. Overall some 41 percent of the households borrowed from MFI sources, compared to only 5 percent that borrowed from formal sources. Some 13 percent of villages have access to commercial banks, while an average 5 MFIs operate in each village, implying a large concentration of microfinance organizations in Bangladesh. Yet 33 percent of MFI borrowers are found to be credit constrained. Interestingly, 32 percent of the households borrowed from a single source and about 10 percent from multiple sources. While 48 percent of households experienced natural calamities, some 9 percent of households lost at least one family member or otherwise incurred losses in their income-generating activities (e.g., loss of a cow), and 4 percent of households had some type of financial losses (e.g., theft) over the three years prior to the survey.

Table 11 presents the fixed-effects estimates of indebtedness (whether a household is indebted, meaning its debt liability is more than 20 percent of income or stock of debt is more than 20 percent of the non-land assets). We have estimates using alternative model specifications (one model uses three-years of panel data and the other two-years of panel data with shock variables). The debt-asset based measure, being a long-term measure of indebtedness, is found to have a declining trend over time.

Among the family characteristics, male-headed households are more indebted than female-headed households in the short-run, but not in the long-run. Similarly, households headed by younger members are more likely to be indebted than those headed by older people in the short-run, but again the age of the household head does not matter for long-run indebtedness. While the education level does not matter in our sample (perhaps because the average schooling of household heads is only 3 years), the dependency ratio (proportion of dependents among the household’s members) matters a lot, irrespective of model specifications: a higher dependency rate means higher indebtedness both in the short- and long-term.

20
# **Appendix 1: Additional Tables and Figures**

# **Table 1.1. Different Definitions of Welfare in Studies on Poverty and Inequality in Russia**

|**_Description_**|**_Definition_**|**_Source/paper_**|**_Data_**|
|---|---|---|---|
|**_Income variable_**||||
|**1.Reported total household**<br>**income**|**_Total_**<br>**_household_**<br>**_monetary_**<br>**_income_**<br>**_(one_**<br>**_question)_**|Lukiyanova and Oshchepkov (2012)|RLMS, 2000-2005|
|||Ferrer-i-Carbonell and Van Praag<br>(2001)|RUSSET,1997-<br>1998|
|||Stillman (2001)|RLMS, 1994-1998|
|**2. Total household income**|Household labor earning + private transfers (or|Lukiyanova and Oshchepkov(2012)|RLMS, 2000-2005|
|**based on the sum of**<br>|net private transfers) + public transfers + capital<br>|Gorodnichenko_et al._ (2010)|RLMS, 1994-2005|
|**components (or disposable**<br>**household income)**|income (+ income from home production)|Mu(2006)|RLMS, 1994-2000|
|||Lokshin and Ravallion(2004)|RLMS, 1994-1998|
|||Commander_et al._ (1999)|RLMS, 1992-1996|
|||Lokshin and Popkin (1999)|RLMS, 1992-1996|
|**3. Individual labor earning**|Money and payment in-kind received from|Lukiyanova and Oshchepkov(2012)|RLMS, 2000-2005|
|**(separately and aggregated**<br>|primary and secondary jobs + money received<br>|Gorodnichenko_et al._ (2010)|RLMS, 1994-2005|
|**at household level)**|from regular economic activities|Skoufias (2003)|RLMS 1994-2000|
|**_Consumption variable_**|||,|
|**4.Non-durable**<br>**expenditures**|Food, alcohol and tobacco + clothing and<br>footwear + gasoline and other fuel expenses +<br> <br> <br> <br>|Gorodnichenko_et al._(2010)|RLMS, 1994-2005|
||rents<br>and<br>housing<br>utilities<br>+<br>services<br>+ti f h fd|Mu(2006)|RLMS, 1994-2000|
||(consumpon o ome-grown oo)|Stillman(2001)|RLMS, 1994-1998|
|||Skoufias (2003)|RLMS, 1994-2000|
|**5. Aggregate expenditures**|Non-durable expenditures + expenditures on<br>|Gorodnichenko_et al._ (2010)|RLMS, 1994-2005|
||durables (+consumption of home-grown food)|Stillman and Thomas (2008)|RLMS, 1994-2000|

50
|**Box 4: How regulators link required revenue and allowed average service price**.<br>The regulation of a monopolist starts with an assessment of the net present revenue it will be allowed to collect<br>over the period during which it is expected to run the business, in such a way that it does not lose money. At<br>any point in time, Required Revenue (RR) is simply the sum of: (i) the net present value (NPV) of operational (or<br>recurrent) expenditure, Investment (or capital) expenditure and the change in the value of assets associated<br>with normal depreciation (negative) and other more market-based changes in value which can be positive or<br>negative. The net asset value is simply the net present value of the investments throughout the period analyzed,<br>accounting for depreciation, including sometimes controversial assessments of the value of the initial asset base.<br>Formally, this can be summarized with the following formula: RRT=∑<br>(�����)<br>(�� �)<sup>�</sup><br>�<br>���<br>+ A0-<br>��<br>(�� �)<sup>�</sup><br>with Gt= Operational costs for year t (OPEX), It= Investments during year t (CAPEX), A0= Initial investment (asset<br>value at the beginning of period),_A_T= End of period asset value which accounts for a fair remuneration of<br>capital),= Discount rate (or cost of capital) and RRT = Net present value of the minimum revenue required by<br>the operator to ensure it does not lose money, to year_T._Each of these variables is a source of tension between<br>a regulator and the operator, whether public or private, simply because each is hard to measure precisely.<br>To estimate this revenue, the costs to be claimed by the firm have to be estimated and accounting data is central<br>to this estimation. This accounting data has to cover both: (i) operational expenditures, i.e. G, (for instance to<br>get a sense of the match between the actual efforts to maintain and the expected maintenance needs) and (ii)<br>the capital expenditures, i.e. I, (to be able to track the efforts made to comply with commitments as well as the<br>effective anticipation of any changes in demand or in technological requirements; for instance, in the context of<br>changes in production technologies to address climate change concern). The accounting data also offers some<br>(although hardly precise enough in a regulatory context) information on the changes in asset valuation and<br>depreciation, both of which are relevant when setting the price.<br>To see how inflating cost leads to higher average tariffs, it is useful to consider the formula used to combine the<br>required revenue estimated from costs (RR) and the sales volume forecast (V) to estimate the average price (P)<br>that the monopolist should be allowed to charge. Formally: RRT= (∑<br>(��∗��)/�<br>�<br>���<br>)<br>where V is the volume of water sold, d is the discount rate and P is the average tariff that the monopolist will be<br>allowed to charge. P is thus the tariff that ensures this equality.<br>Overall, the approach, thus, ensures that the full, efficient costs of providing the regulated services are measured<br>and monitored in a rigorous and transparent way.|
|---|

34
Figure 3 provides a first attempt at answering this question. In particular, it looks at the discrepancy between standard measures of diversification, based on cross-sectional export baskets, and our proposed empirical approximation of latent export baskets by plotting the proposed approximation of the number of latent export lines, Nc,TL , on the y axis and the average number of goods exported by a country from _t_ o until _T_ , Nc,T<sup>, on the x axis, where we choose</sup><sup>_t_o=1972 and</sup><sup>_T_=2012.15 The 45 degree line benchmarks the</sup> expected relationship between the two indicators of diversification if a country holds a constant export basket at each point in time.

Figure 3 shows that there is indeed a sizeable difference between traditional measures of diversification and latent diversification, especially for countries with few export products per year. Moreover, the gap between the two measures of diversification is largest for countries with an average of 200 to 300 active export lines per year, numbers that are not far from the number of products exported by the average country in the world identified in Figure 1. In contrast, the bias in favor of concentration present in standard measures of diversification is less severe for countries with large export baskets, giving the concave shape to the curve as we move to the northeast on the graph. The latter observation should not come as a surprise given the nature of the trade data—any empirical measure of the extensive margin of exports will have an upper bound set by the number of product lines in the SITC classification.

The differences between the proposed empirical approximation of latent export lines and standard measures of the extensive margin of exports are further illustrated by the dynamics of the two measures of diversification. Figure 4 plots the coefficients on the year fixed effects obtained from the following regression: where yc,t = {Nc,tL , Nc,t} , θ is a constant, αc is a country fixed effect, τt is a year effect, and εc,t is an error term. The year fixed effects are relative to the averages in 1972.

The evidence presented in Figure 4 is clear—the process of trade diversification depicted by the number of latent export lines is much more dramatic than that presented by standard measures of the extensive margin of exports. On average countries accumulated approximately 350 export lines in their basket of

> 15 We decided to start our analysis in 1972, instead of 1962 when trade data is first available, because coverage improves over time. Starting in 1972 gives a sufficiently long time period while ensuring better cross-country coverage.

14
# **Table 13**

# **Determinants of the Return on Assets: IV Estimation**

The dependent variable is _Return on assets. Return on assets_ is defined as profit before tax as a percentage of total assets of a bank. _Fee income_ is the share of non-interest income in total operating income. _Non-deposit funding_ is the share of non-deposit short-term funding in total deposits & short-term funding. _Assets_ is the natural logarithm of total assets in US $. _Equity_ is the capital to asset ratio, which is defined as equity as a percentage of total assets. We used one period lag of equity in the regressions. _Assets growth_ is the inflation-adjusted growth rate of bank assets. _Overhead_ is defined as overheads as a percentage of total assets. the data for these bank level variables are obtained from Bankscope. _Inflation_ is the inflation rate based on consumer prices. _GDP growth_ is the inflation adjusted growth rate of GDP per capita of the country. _GDP per capita_ is in thousands of 2000 constant US$. All these macroeconomic variables are from World Development Indicators (WDI) of World Bank. The regressions in Panel A use instruments for the _Fee income_ variable, and the regressions Panel B use instruments for the _Nondeposit funding_ variable. The regressions in column 1 use as instruments dummy variables indicating whether the bank is an investment bank, a non-bank credit institution, or a bank in the other category. The regressions in column 2 use as instruments dummy variables indicating in 2001 whether the bank is an investment bank, a non-bank credit institution, or a bank in the other category. Other data are for 2002-2007. We estimate all regressions using country and time fixed effects. We also report the coefficient estimates for the instrumental variables of the first-stage regression, the p-value of the F-test of joint significance of identifying instruments, the p-value of the Hausman specification error test which compares the difference between the IV and OLS estimators, and the p-value of the Hansen J-test of overidentifying restrictions. Standard errors are in parentheses. *, ** and *** denote significance at 10%, 5% and 1%, respectively.

|_Panel A_|(1)|(2)|
|---|---|---|
||IV: Bank category|IV: Bank category 2001|
|Fee income share|0.035***|0.039***|
||(0.005)|(0.006)|
|Assets|-0.000|-0.000|
||(0.000)|(0.000)|
|Equity|0.076***|0.079***|
||(0.004)|(0.005)|
|Assets growth|0.010***|0.010***|
||(0.002)|(0.002)|
|Overhead|-0.159***|-0.200***|
||(0.012)|(0.014)|
|Inflation|0.134***|0.123**|
||(0.037)|(0.055)|
|GDP growth|0.114***|0.091**|
||(0.030)|(0.046)|
|GDP per capita|0.000|0.000|
||(0.001)|(0.001)|
|_First-stage_|||
|Instrumental variables|||
|Investment bank dummy|0.289***|0.284***|
||(0.009)|(0.011)|
|Non-bank credit institution dummy|-0.021|-0.012|
||(0.013)|(0.014)|
|Other dummy|-0.031***|-0.020|
||(0.012)|(0.013)|

51
count on an annual incidence of such cargo in the order of 18 millicn tons by 1990, 25 million tons by 1995 (the end of the 8th Five-year Plan), and 32 million tons by the turn of the century.

9. Containerization of India's trades has started with much delay and at a slow pace. The reasons are explained in the following secticrs. During 1987-1988, a total of 5.3 million tons of cargo was handled in containers. What was the previous growth record?

Growth of Containerized Trades in India

|Period|Million tons|
|---|---|
|1980-81|1.4<br>|
|1981-82|2.0|
|1982-83<br>|2.1<br>|
|1983-84|2.2<br>|
|1984-85|3.3|
|1985-86|4.0|
|1986-87|4.5|
|1987-88|5.3|

(Note: The average annual growth rate was 21 percent).

# **Source: Indian Ports Association.**

**10.** Despite the high annual growth rates, the penetration of containers in the general cargo market is still relatively low. The 5.3 million tons of containerized cargo handled during 1987-1988 represents less than one third of the total incidence of containerizable cargo during that period. The target under the 7th Five-year Plan was 5C percent container penetration of national general cargo trades.

|Penetrat|ion of Conta<br>|iners in Gene<br>|ral Cargo Traffic<br>|
|---|---|---|---|
||through key|Indian Ports|(1987-88)|
|Port|Import<br>......|s<br>Expor<br>.<br>.(percent|ts<br>Total<br>age<br>share).|
|Bombay|23|61|<br>32|
|Madras|25|58|<br>34|
|Calcutta|10|34|<br>17<br>|
|Kandla|11|29|<br>18|
|Cochin|22|63|<br>45|
|Haldia|38|100|<br>63|
|Tuticorin|<br>26|17|<br>22|
|Total|20|49|<br>°8|

**Source: Annual report of** the individual **ports.**
43 wealth uneven. The _way_ in which the housing stock was privatized also contributed, to begin with, to making the distribution of wealth more uneven, since housing was often sold at prices below market values to groups of citizens with income and wealth above the average – another example of “asset stripping”. However, in recent years, as the ownership of housing has gradually broadened, the distribution of housing wealth has tended to become somewhat more even (UNDP, 2005).

It is not self-evident that the income and wealth gaps will continue to widen in the upcoming decades. One reason is that the modernization of production is likely to spread across firms and across regions, so that China may begin to slide along the downwardsloping (rather than the upward-sloping) section of the Kuznetz curve. Indeed, already today, there is a tendency for the modernization process to spread to a number of interior provinces (Agarwala, 2002), although it is unlikely that _all_ provinces will take part in this process to the same extent.<sup>83</sup> The future development of the overall distribution of income in the country depends also crucially on what happens to productivity in agriculture and the relative price of agriculture products – in the same way as these factors dominated the development of the distribution of income in the early 1980s. Moreover, further expansion of Chinese exports of labor-intensives products may, in itself, favor workers with modest skills, although the highly elastic supply of such labor, and perhaps also the absence of traditional labor unions, tends to dampen the positive effects on wages for lowskilled workers.<sup>84</sup> But what will actually happen to the distribution of income in China during the coming decades depends, of course, also on what type of economic and social policies that will actually be pursued in the country – in the same way as the development of the distribution of income in recent decades partly is a result of specific policy measures during that period.

Let us turn from China’s social development in terms of income and wealth and their distribution to the provision of _human services_ , such as education and health care. China made considerable achievements in these fields already in the pre-reform period 1950-

> 83 On the basis of their study, Brun et al. (2002) argue that the spatial spillovers have been confined to coastal regions. By contrast, Luo (2005) argues, on the basis of provincial panel data from 1978 to 1999, that there have been large spillover effects on the entire Chinese economy due to the rapid expansion of the coastal provinces, but that these spillover effects have not been strong enough to prevent a widening of regional (relative and absolute) per capita income gaps.

> 84 For a survey of the rather ambiguous results in the literature on the distributional consequences of increased openness to international trade, see, for instance, Wei and Wu (2003).
Policy ReseaRch WoRking PaPeR 4635

# **Abstract**

Is the vast army of the self-employed in low income countries a source of employment generation? This paper uses data from surveys in Sri Lanka to compare the characteristics of own account workers (non-employers) with wage workers and with owners of larger firms. The authors use a rich set of measures of background, ability, and attitudes, including lottery experiments measuring risk attitudes. Consistent with the International Labor Organization’s views of the self employed (represented by Tokman), the analysis finds that two-thirds to threequarters of the own account workers have characteristics which are more like wage workers than larger firm owners. This suggests the majority of the own account workers are unlikely to become employers. Using a two and a half year panel of enterprises, the authors show that the minority of own account workers who are more like larger firm owners are more likely to expand by adding paid employees. The results suggest that finance is not the sole constraint to growth of microenterprises, and provides an explanation for the low rates of growth of enterprises supported by microlending.

This paper—a product of the Trade Team, Development Research Group—is part of a larger effort in the department to study microenterprise dynamics. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The author may be contacted at dmckenzie@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
Kunreuther, Howard and Anne E. Kleffner (1992), Should earthquake mitigation measures be voluntary or required? _Journal of Regulatory Economics_ , 4, 321-333.

- Kunreuther, Howard and Richard J. Roth (1998),Paying the Price: The Status and Role of Insurance Against Natural Disasters in the United States, Joseph Henry Press.

- Kunreuther, Howard and Anne Kleffner (1992), Should Earthquake Mitigation Measures Be Voluntary or Required?” _Journal of Regulatory Economics_ , vol. 4: 321-333.

- Laffont, David. 1994 (The New Economics of Regulation Ten Years After, _Econometrica,_ vol. 62, no. 3: 507-537.

- Laffont, Jean-Jacques and David Martimort (2002), _The Theory of Incentives: The PrincipalAgent Model._ Princeton University Press, Princeton.

- Lall, Somik V. and Uwe Deichmann (2006), “Fiscal and distributional implications of property tax reforms in Indian cities” _Economic and Political Weekly_ , July 22, 2006, pp 32093220.

- Lall, Somik V., A. Suri and Uwe Deichmann (2006), Household savings and residential mobility in informal settlements in Bhopal India, _Urban Studies_ , 43, 7, 1-15

- Lall, Somik, Uwe Deichmann, Mattias Lundberg and Nazmul Chaudhury (2004), Tenure, diversity, and commitment: Community participation for urban service provision, _Journal of Development Studies_ , 40, 3:1-26

- Lall, Somik V., Mattias Lundberg, and Zmarak Shalizi (2008), “Implications of alternate policies on welfare of slum dwellers: Evidence from Pune, India.” _Journal of Urban Economics_ , 63, 56-73.

- Lancaster, K.J. (1966), A new approach to consumer theory, _Journal of Political Economy_ 74, 132–157.

- McGranahan, Gordon, Deborah Balk and Bridget Anderson (2007), The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones, _Environment and Urbanization_ , 19, 1: 17-37.

- Montgomery, Mark R. (2009), Book review of World Development Report 2009: Reshaping Economic Geography, _Population and Development Review_ , 35, 1:197-208.

- Muth, R.F. (1969), _Cities and Housing: The Spatial Pattern of Urban Residential Land Use_ . University of Chicago Press, Chicago.

- Nakagawa, Masayuki, Makoto Saito and Hisaka Yamaga (2007), Earthquake risk and housing rents: evidence from the Tokyo Metropolitan Area, _Regional Science and Urban Economics,_ vol. 37: 87-99.

- OECD (2004), _Large scale disasters - lessons learned_ , Organisation for Economic Co-operation and Development, Paris.

- Onder, Zeynep, Vedia Dokmeci, and Berna Keskin (2004), The Impact of Public Perception of Earthquake Risk on Istanbul’s Housing Market. _Journal of Real Estate Literature_ . 12, 2.

- Organization for Economic Co-operation and Development (2008), Costs of Inaction on Environmental Policy Challenges: Summary Report, ENV/EPOC(2007)17/REV2. URL available: <u>http://www.oecd.org/dataoecd/60/45/40501169.pdf</u>

- Oster, Emily (2005), Sexually Transmitted Infections, Sexual Behavior and the HIV/AIDS Epidemic, _Quarterly Journal of Economics,_ vol. 120, no. 2: 467-515.

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