rafmacalaba/datause-encoder-data huggingface dataset:
**TABLE 8: Investment financial performance and capital market development.** The dependent variable is the investment-level PME vs. S&P 500. Explanatory variables are measured in the year of first cash flow, and have been normalized as Z-scores by subtracting off the sample mean and dividing by the sample standard deviation. All columns include country fixed effects (a version without fixed effecs is provided in Table A10). The de jure financial openness index is the first principle component of dummy variables that codify the restrictions on cross-border financial transactions reported in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER). Private sector credit is domestic private credit to the real sector by deposit money banks. Standard errors are clustered at the country-year. *** p<0.01, ** p<0.05, * p<0.1

||(1)|(2)|(3)<br>Qua|(4)<br>ntile Regr|(5)<br>ession|(6)|
|---|---|---|---|---|---|---|
||OLS|0.1|0.25|0.5|0.75|0.9|
||PME|PME|PME|PME|PME|PME|
|Panel A) Direct investments, vintage|pre-201|0|||||
|De-jure fnancial openness index|-0.10|0.00|0.02|0.06|0.14|-0.60***|
||(0.52)|(0.03)|(0.04)|(0.06)|(0.11)|(0.14)|
|Private sector credit (% of GDP)|-1.33|-0.00|-0.03|-0.15**|-0.27|-0.73***|
||(0.92)|(0.03)|(0.06)|(0.06)|(0.18)|(0.23)|
|Constant|1.72|-0.00|-0.01|0.11|0.42|2.08***|
||(1.21)|(0.09)|(0.10)|(0.20)|(0.31)|(0.56)|
|R-squared|0.1791|0.0012|0.0160|0.1031|0.1674|0.1706|
|Number of observations|1,093|1,093|1,093|1,093|1,093|1,093|
|Panel B) Fund investments, vintage|pre-2010||||||
|De-jure fnancial openness index|0.17|0.08|-0.04|-0.09|-0.17|-0.03|
||(0.72)|(0.12)|(0.11)|(0.16)|(0.26)|(0.11)|
|Private sector credit (% of GDP)|-3.10|-0.16|-0.22**|-0.16|-0.52**|-0.72***|
||(2.49)|(0.13)|(0.09)|(0.20)|(0.25)|(0.27)|
|Constant|2.56|-0.01|-0.22|0.44|-0.05|-0.21|
||(1.68)|(0.53)|(0.31)|(0.44)|(0.38)|(0.33)|
|R-squared|0.2831|0.0016|0.0004|0.0413|0.0408|0.2532|
|Number of observations|142|142|142|142|142|142|
|Country fxed efects|Yes|Yes|Yes|Yes|Yes|Yes|

39
# Agricultural Policy and Food Security

The discussion so far has focused on domestic concerns. We now turn to international dimensions of agricultural policy. The past decade has experienced a worrisome rise of protectionism—in spite of the ongoing World Trade Organization Doha Round of trade talks, launched in 2001, meant to foster trade liberalization, which put developing country needs at the top of the agenda. Both developed and developing countries maintain high protection for agriculture, which creates a drag on developing countries‘ agricultural exports. In addition, in the name of food security, some countries have reacted to food price increases with additional protectionist policies, such as export bans in Vietnam and India.

# _Market Distorting Policies of Developed Countries_

Trade flows have grown more than twice as fast as aggregate GDP over the past 30 years. The developing world‘s share of global trade increased from about one-quarter to more than onethird and the composition of their exports has been upgraded. For a long time they were exporters of primary commodities and importers of manufactured goods, but over the past two decades they have moved strongly into manufactured exports. The export share of developing countries in global manufacturing exports was 20 percent in 1990/91 and rose to 42 percent in 2006/07. For agricultural exports the numbers are 32 percent and 41.5 percent, respectively. Moreover, trade among developing countries also gained importance. While 4 percent of global manufacturing exports went from developing countries to other developing countries in 1990/91, it increased to 20 percent in 2006/07. For agriculture, the corresponding numbers are 7 percent and 20 percent (Aksoy and Ng 2010).

Despite these changes and several rounds of trade liberalization, many developing countries have been unsuccessful in integrating with the world economy. Nearly all the growth in developing country shares of trade has been driven by middle-income countries. By contrast, the 49 least-developed countries—most of which are in Africa—have gained no market share at all. Moreover, some regions have seen much smaller shifts in the composition of their exports. The manufactured share of merchandise exports is 80–90 percent in East and South Asia but only 60 percent in Latin America. Africa and the Middle East have yet to reach the 30 percent mark, and 35
|Governance: Govt. effectiveness<br>_Government Effectiveness_|OLS<br>PLREG|1.718<sup>***</sup>|_0.653_|7.041|2.725<sup>***</sup><br>1.823<sup>***</sup>|_0.829_<br>_0.275_|2,082<br>2,081|
|---|---|---|---|---|---|---|---|
|_index_|OLS Fixed Effect<br>PLREG Fixed<br>Effect|1.498<sup>***</sup>|_0.261_|5.155|-0.569<br>-0.512<sup>*</sup>|_0.431_<br>_0.278_|2,082<br>2,081|
|Governance: Domestic|OLS|3.130<sup>***</sup>|_0.582_||0.288<sup>***</sup>|_0.069_|2,039|
|resources||||||||
|_Tax revenues over GDP_|PLREG<br>OLS Fixed Effect|1.237<sup>***</sup>|_0.280_|19.076|0.272<sup>***</sup><br>-0.004|_0.090_<br>_0.035_|2,038<br>2,039|
||PLREG Fixed<br>Effect|||3.866|0.018|_0.019_|2,038|
|Technology 1|OLS|4.269<sup>***</sup>|_0.564_||-0.014|_0.009_|2,053|
|_Mobile phone suscriptions_|PLREG|||30.470|-0.006|_0.004_|2,052|
|_per 100 inhabitants_|OLS Fixed Effect<br>PLREG Fixed<br>Effect|0.694|_0.518_|4.325|0.010<sup>**</sup><br>0.013<sup>**</sup>|_0.004_<br>_0.002_|2,053<br>2,052|
|Technology 2|OLS|2.375<sup>***</sup>|_0.718_||0.063<sup>***</sup>|_0.018_|2,015|
|_Percentage of population_|PLREG|||11.346|0.035<sup>***</sup>|_0.008_|2,014|
|_that uses the internet_|OLS Fixed Effect|-0.480|_0.653_||0.038<sup>***</sup>|_0.010_|2,015|
||PLREG Fixed<br>Effect|||3.451|0.039<sup>***</sup>|_0.005_|2,014|
|Demographics|OLS|1.220<sup>***</sup>|_0.424_||0.790<sup>***</sup>|_0.069_|2,329|
|_Share of the population_|PLREG|||4.816|0.721<sup>***</sup>|_0.024_|2,328|
|_age 65+_|OLS Fixed Effect<br>PLREG Fixed<br>Effect|1.382<sup>***</sup>|_0.262_|5.174|0.027<br>0.001|_0.037_<br>_0.042_|2,329<br>2,328|
|Selective reporting|OLS<br>PLREG|3.064<sup>***</sup>|_0.152_|18.636|||2,376<br>2,375|
||OLS Fixed Effect|1.316<sup>***</sup>|_0.294_||||2,376|
|Note:Standard errors are clustered at t|PLREG Fixed<br>Effect<br>he country level. All sub|-function tests are|significant at p<|5.603<br>0.001 level. The c|orrection forselect|ive reportingus|2,375<br>es a cubic|

<u><mark>Note: Standard errors are clustered at the country level. All sub-function tests are significant at p<0.001 level. The correction for selective reporting uses a cubic</mark></u> <mark>function of the p-score.</mark> 39
# **Table 4.1: Estimates of the marginal cost of public funds (MCPF), different countries and tax types**

||**High**|**-income countries**||
|---|---|---|---|
|Country|Tax type|MCPF estimate|Study|
|Australia|Labor|1.19-1.24|Campbell-Bond (1997)|
|Australia|Labor|1.28-1.55|Findlay-Jones (1982)|
|Australia|Capital|1.21-1.48|Diewert-Lawrence (1998)|
|Australia|Capital|1.15-1.51|Benge (1999)|
|Canada|Commodity|1.25|Campbell (1975)|
|Canada|Labor|1.38|Dahlby (1994)|
|Canada|Labor|1.39-153|Fortin-Lacriox (1994)|
|New Zealand|Labor|1.18|Diewert-Lawrence (1994)|
|Sweden|All taxes|1.69-2.29|Hansson-Stuart (1985)|
|United States|All taxes|1.17-1.33|Ballard et al (1985)|
|United States|All taxes|1.47|Jorgenson-Yun (1990)|
|United States|Labor|1.21-1.24|Stuart (1984)|
|United States|Labor|1.32-1.47|Browning (1987)|
|United States|Labor|1.08-1.14|<br>Ahmed-Croushore (1994)|
||**Low**|**-income countries**||
|Bangaldesh|Sales|0.95-1.07|Devarajan et al (2001)|
|Bangladesh|Import|1.17-2.18|Devarajan et al (2001)|
|Cameroon|Sales|0.48-0.96|Devarajan et al (2001)|
|Cameroon|Import|1.05-1.37|Devarajan et al (2001)|
|China|Sales|2.31|Laffont et al (1997)|
|India|Excise|1.66-2.15|Ahmad and Stern (1987)|
|India|Sales|1.59-2.12|Ahmad and Stern (1987)|
|India|Import|1.54-2.17|Ahmad and Stern (1987)|
|Indonesia|Sales|0.97-1.11|Devarajan et al (2001)|
|Indonesia|Import|0.99-1.18|Devarajan et al (2001)|

Sources: Various (see references in right-hand column).

Our more specific concern here is the MCPF in developing countries, its level and how it varies with tax type. The lower part of Table 4.1 gives some indication on this. Although the numbers are rather widely varying (and, in some cases, somewhat untrustworthy, as when they are substantially below unity), they seem to indicate that excise, sales and import taxes all imply substantial deadweight losses at least in some cases. It is however difficult from this table to distinguish clearly between tax types, in terms of which of these taxes ought, if possible, to be reduced.

A comprehensive study of African economies, Warlters and Auriol (2005), is summed up in Table 4.2. Virtually all the African economies are included in this study (numbers included in the table are only for the subset of most significant countries), and with indications of marginal distortions for all five major categories of taxes: indirect domestic taxes, including sales taxes, excise taxes and VAT; export taxes; import taxes; and taxes on factors of production: capital, and labor. The general result of this study is that domestic taxes and import taxes appear to be relatively non-distortive, while capital and labor taxes are more distortive. One reason why capital taxes (in the study, largely represented by formal corporate tax rates) are highly distortive is high capital mobility implying that tax competition factors are significant for this loss. The main reason for high deadweight losses due to labor taxes is rather the existence of an informal sector (with, typically, labor productivity substantially below that of the formal sector), to which labor would move when taxes are set too high.

18
Policy Research Working Paper 7924

# **Abstract**

The majority of enterprises in many developing countries have no paid workers. This paper reports on a field experiment conducted in Sri Lanka that provided wage subsidies to randomly chosen microenterprises to test whether hiring additional labor would benefit such firms. In the presence of labor market frictions, a short-term subsidy could have a lasting impact on firm employment. Using 12 rounds of surveys to track dynamics four years after the end of the subsidy, the study finds that firms increased employment during the subsidy period, but there was no lasting impact on employment, profitability, or sales. Two supplementary interventions and treatment heterogeneity suggest the lack of impact is not due to complementarities with capital or management skills, and detailed survey data help rule out a number of theoretical mechanisms that could result in sub-optimally low employment. The study concludes that the urban labor market facing microenterprises does not have large frictions that would prevent own-account workers from becoming employers.

This paper is a product of the Finance and Private Sector Development Team, Development Research 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 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
As a result of the above factors taken together, women have fewer assets and lower capacity for mobilizing resources than do men. This is compounded by lower access to credit and to most public and private services which also tend to favor men: extension agencies, credit, institutions allocating agricultural inputs and outputs, marketing boards, fertilizer programs, contract farming schemes etc. In some cases, access to private transfers and informal networks may be less differentiated across gender. In a study of northern Mali, Christiaensen and Boisvert (2000) find that female-headed households are less vulnerable to drought shocks in part due to community solidarity which more readily kicks in for them. In particular, widows and married women may have access to support from brothers or uncles. Official food aid and family food transfers are found to provide significant insurance mechanisms. However, these results may not be generalizable to all of Mali. Elsewhere in West Africa, where similar questions have been posed, the opposite has been found. For example based on fieldwork in Ghana and Côte d‘Ivoire, MacLean (2010) identifies patterns of reciprocity and gift giving within and across families and shows that the elderly and women participate less in them than the young and male, and thus tend to rely more on formal systems of social security than informal ones.

Using rural household data collected by IFPRI in Mali‘s Zone Lacustre, a few studies have examined the degree to which shocks are reflected in consumption (Skoufias and Quisumbing 2003; Harrower and Hoddinott 2004). Harrower and Hoddinott find that idiosyncratic shocks such as the illness of a prime age adult household member are not reflected in household per capita consumption regardless of the gender of the shock‘s recipient. However, this does not reveal whether actual individual consumption alters differentially by gender following a shock as one study found was the case in rural Southern Ethiopia. Dercon and Krishnan (2000) document imperfect risk-sharing between spouses whereby wives loose much more weight than husbands following a negative shock.

In sum, men and women may be exposed to different risks both in terms of the type and extent of the risks they face. They will also have widely different capacities to cope with risks even within the same household (Dercon and Krishnan 2000). Formal social protection remains under-developed and piecemeal in Mali. As one might expect in a poor rural and agriculturebased economy like Mali, agro-climactic shocks are recurrent and a major concern. Naturally, most of the country‘s and donors‘ safety net programs address food security and are food based. The country maintains cereal banks and engages in public stock manipulation. Universal tax and 8
# Appendix Table 3 Characteristics of Rate Cycles over Time

||Durat|ion|Number o<br>Chan|f Rate<br>ges|Pac<br>(pp/cha|e<br>nge)|Veloc<br>(first 6 m|ity<br>onths)|Ampli<br>(in p|tude<br>p)|
|---|---|---|---|---|---|---|---|---|---|---|
||Tightening|Easing|Tightening|Easing|Tightening|Easing|Tightening|Easing|Tightening|Easing|
|Full Period|47.2|78.7|14.3|16.9|1.0|-0.6|1.7|-2.6|7.7|-7.7|
|Pre-ECB:<br>1970-98|49.9|65.6|16.2|20.1|1.2|-0.7|1.8|-2.1|8.9|-9.3|
|Post-ECB:<br>1999-2024|35.1|109.3|9.2|11.8|0.3|-0.4|1.0|-1.6|2.8|-4.2|
|1970-1984|54.9|48.3|16.7|13.8|1.3|-1.0|2.2|-2.8|9.6|-7.5|
|1985-1998|39.2|71.4|12.5|21.7|0.9|-0.7|1.6|-2.0|6.2|-9.4|
|1999-2007|38.1|62.6|9.7|12.2|0.3|-0.4|0.9|-1.4|2.7|-4.3|
|2008-2019|36.1|125.2|8.1|11.3|0.3|-0.4|0.6|-1.6|2.1|-4.0|
|2020-2024<br>(May)|27.4|120.2|10.5|10.2|0.4|-0.4|1.6|-1.4|4.2|-3.4|
|Change or<br>percent<br>change<br>from 1970-<br>84<br>period<br>to 2008-19<br>period|||||||||||
|Change<br>|-18.7|77.0|-8.6|-2.4|-1.1|0.6|-1.6|1.2|-7.5|3.5|
|%<br>Change|-0.3|1.6|-0.5|-0.2|-0.8|-0.6|-0.7|-0.4|-0.8|-0.5|

Sources: Authors’ calculations using the turning points for rate cycles listed in Appendix Table 1 and data ending on May 31, 2024. Notes: This table shows averages across all tightening or easing phases within the given time period, The number and pace of rate adjustments only include "in-sync" rate adjustments. Velocity and amplitude are the total change in rates (in any direction) over the first six months of the phase or entire phase, respectively. Averages are calculated for each economy, and then over the sample as a whole. Members of the euro area are included as individual countries through 1998, and then the ECB cycle is included from 1999.

# Appendix Table 4 Variance Contributions of Global Factors

(Percent of total variation, averages across countries)

|Global factors|70-23|70-98|99-24|70-84|85-98|99-07|08-19|20-24|
|---|---|---|---|---|---|---|---|---|
|Interest Rates|13.4|11.4|38.1|9.6|10.7|30.8|29.3|38.4|
|Inflation|21.5|9.6|32.0|11.2|13.1|22.0|23.7|34.3|
|Output growth|23.6|6.5|39.7|7.1|10.7|15.7|13.2|46.9|

Sources: Authors’ calculations based on data from January 1970 – March 2024. Notes: The table presents the average contributions of the global rate factor, the global output factor, and the global inflation factor to the variance of country-specific policy rates, inflation, and output growth, respectively, over the periods as noted in the second row. See Appendix Table 2 for variable definitions.

84
FIGURE 1: MEXICO - GROSS PRIVATE AND PUBLIC SECTOR INVESTMENT TO GDP RATIOS <!-- Start of picture text --> 15.0-<br>12.5-~ 1 -<br>10-0-<br>.v ~~~~ I l l i l i l I PUBLIC' i a f<br>l9*vO 1965 1970 1975 1980 1985<br>(in percent)<br><!-- End of picture text -->
Table A25: Robustness of impact on SRH knowledge index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimming|treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.31**|0.36***|0.30**|0.30**|0.30**|0.30**|0.31***|
|||(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T1|+Leaders|0.21*|0.45***|0.10|0.17|0.17|0.19*|0.21*|
|||(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|(0.12)|
|T2|(Safe Spaces + IGA)|0.31***|0.48***|0.27**|0.29**|0.29**|0.29**|0.30**|
|||(0.12)|(0.10)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T2|+Leaders|0.18|0.45***|0.10|0.14|0.14|0.16|0.18|
|||(0.12)|(0.09)|(0.12)|(0.11)|(0.11)|(0.11)|(0.12)|
|T3|(Safe Spaces + Husbands Clubs)|0.35***<br>(0.12)|0.56***<br>(0.11)|0.26**<br>(0.11)|0.30***<br>(0.11)|0.30***<br>(0.11)|0.32***<br>(0.11)|0.34***<br>(0.12)|
|T3|+Leaders|0.23<br>(0.15)|0.31**<br>(0.14)|0.20<br>(0.15)|0.22<br>(0.15)|0.22<br>(0.15)|0.22<br>(0.15)|0.23<br>(0.14)|
|T4|(control spillover)|0.01|0.01|0.01|0.01|0.01|0.01|0.01|
|||(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|N||2953|2952|2952|2954|2954|2954|2953|
|Con|trol Mean|0|0|0|.001|.001|.001|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

57
ends up in the second, preferred equilibrium depends on the extent to which donors and recipients recognize the adverse effects of aid. on learning-by-doing.

While we have emphasized tax efficiency, the argument can be applied in other areas. For example, suppose that learning-by-doing spillovers are concentrated in the recipient's nascent manufacturing sector, and that manufactured goods are traded internationally (Bruton [1998]). In the absence of other fonns of financing, a rise in aid will produce a rise in expenditure and a fall in production (the mediating variable being the real exchange rate). If learning-by-doing spillovers are associated with accumulated production experience in the manufacturing sector, aid will again be too large when these spillovers are ignored. Manufacturing output will in turn be too small and the rate of learning-by-doing correspondingly sub-optimal. As in our case, graduation will be postponed or prevented altogether.

In section 2, we describe and solve the model, and then use it in section 3 to develop a precise interpretation of aid dependence. In a concluding section we investigate the implications of the analysis for aid policy and discuss some extensions.

# **2. The Model**

In the absence of foreign aid, governments optimize by equating the marginal social benefit of public spending to the marginal social cost of public funds. Equivalently, the government implements all spending projects that pass the social cost-benefit test given the existing set of tax instruments and iinancing sources. In Figure 2, the "autarky" optimum is at point 1, with net social benefit given by the triangle _B] 0._ Now suppose that foreign aid is available in amount a to fill the gap between desired spending g and domestic revenue _r._ 'Ihe net social benefit, or surplus, enjoyed by the recipient, gross of any cost of the aid, is now the difference between the areas _OB3g_ and _002r._ Note that this area is always greater than _BIW._ Using slopes of 1 and -1 for simplicity, we can define the surplus as (1) _S(r, g, B, 0) = (Bg - g') - (Or +r_ 2 2 With this setup it is straightforward to study the recipient's optimal response to foreign aid, whether provided as a grant or sas concessional financing (e.g., Kimbrough [1987]). Missing from such accounts, however, is a characterization of institutional development in the recipient's public sector. Yet, several observers have pointed to the pernicious effects of foreign aid on the recipient's ability to develop an effective public revenue and expenditure system (Botchwey and Brautigam [1998], World Bank [1998]). In a widely quoted speech in 1993, Kim Jaycox, the World Bank's then vice president for Africa, said "...donors and African governments together have in effect undermined capacity in Africa: they are undermining it faster than they are building it. .. " 4