rafmacalaba/datause-encoder-data huggingface dataset:
**Table 33 BKD Estimated Annual Lendinga**

Information on total annual lending was not available. The data in Table 33 above are estimates of annual lending derived by multiplying lending during the month of December of each year by 12. Using this rough approximation, lending grew from Rp. 232 million (US$ II million) in 1993 to Rp. 305 million (US$131 million) in 1996. The program issued approximately 1,760,000 loans in 1996, up slightly

|||<br>**1993**|**1994**|**1995**|<br>**1996**|
|---|---|---|---|---|
|**Nominal lending**<br>**volume(RI). million)**|232.312|256.847|258.589|305.330|
|<br>**Gronth in real**|**8**|2|**-8**|9|
|<br>**lending volumc**<br>**(p)ercent)**<br>_<br>|<br>_<br>_<br>_<br>_<br>|<br>__<br>_<br>_<br>_<br>|<br>||
|Nominal**lending**<br>volume(USS)|110.624.920|117.819.793|113.416.15|130.698.739|
|Number of loans<br>issued|1.713.336<br>____|<br>1.639.104<br>_|<br>1.606.884<br> <br>_|1.757,028|
|**Growthin**number of<br>**loans issued(percent)**|<br>3||-2||

ai Estiinates arc derived bv iiultiplying the lending volume in December of each car by 12.

from 1.713,000 in 1993. The real volume of lending grew in each vear except 1995.

Total savings under the program stood at Rp. 23 billion (US$9.8 million) at the end of 1996. In real terms, savings have grown slowly but consistently since 1993. The volume of outstanding savings was equal to about 26 percent of total outstanding loans et f likely net default in 1996.

**Table 34 BKD Required and Voluntarv Savings**

||1993|**19941**|**1995**|<br>**1996**|
|---|---|---|---|---|
|Total nominal savings**(RI).**<br>million)|16.053|<br>18.2391<br>l|20.070|22.827|
|<br>Growth in real savings<br>(perent)<br>|4<br>|_<br>_51_<br>|1<br>|_5_<br>|
|Total nominal savings (US$)<br>|7.644.063<br>|8.366.4881<br> <br>|8.802.67<br>|9.771.259<br>|
|Total savings percent of total<br>outstanding loans|25.1|<br>25.21<br>i|24.6|25.7|
|**Voluntary saiings percent of**<br>net**loansa**|5.4|5.3!<br>.|4.8|4.9|
|<br>**Voluntarv savings real**<br>**growth rate(percent)**|3.2|1.61<br>.|<br>b.2|0.5|

**a< The** volume of voluntary savings is compared to that of outstanding loans net of required savings because in practice. savings required to obtain a loan are equivalent to borrowers receiving a smaller loan. Thus, comparing voluntary savings to loans net of required savings allows an analysis of the importance of voluntary savings in funding loans.

That figure has been constant over the last four vears. BKD units have offered voluntary savings products since 1991. Since 1993, voluntary savings have been equal to about 5 percent of outstanding loans net 79
the strongest relationships with our branch penetration variables, we aim to further underscore the plausibility of our results as reflecting the effects of competition.

# _Data_

We combine data on bank penetration from 99 developed and developing countries from Beck, Demirguc-Kunt, and Martinez Peria (2007) with data from 346 leading microfinance institutions from 67 developing countries. Country coverage is not perfectly overlapping across the two data sets, and missing data for some of the control variables in our regressions further reduces the sample. We are therefore left with 342 observations from 238 microfinance institutions in 38 developing countries in our largest regressions that incorporate bank penetration variables.

The data on microfinance institutions were collected by the Microfinance Information eXchange (or the MIX), a not-for-profit private organization that aims to promote information exchange in the microfinance industry. These data include outreach and impact data, financial data, audited financial statements, and general information on specific microfinance institutions for 346 microfinance institutions in 67 developing countries.<sup>7</sup> These institutions are large by the standards of the microfinance industry, with nearly 18 million active microfinance borrowers and a combined total of $25.3 billion in assets (in purchasing power parity terms). Participation by microfinance institutions in the MIX is voluntary, and thus the sample is skewed toward institutions that have stressed financial objectives and profitability. We expect that these are more likely to compete with banks than are smaller, less profit-oriented microfinance institutions, and thus are well suited to the analysis we undertake below.

The microfinance data are collected for publication in the _Microbanking Bulletin_ (MBB) and have been adjusted to help ensure comparability across institutions when

> 7 This is a substantial increase over the MIX database used in Cull, Demirgüç-Kunt, and Morduch (2007), which contained information from 124 MFIs in 49 countries. That data set was a variant of the so-called MBB 9 database. In this paper, we use a variant of the MBB 10 database. There are 540 observations in our database because some MFIs report information for multiple years.

9
number of continuous days after suffering an illness in day 1.<sup>7</sup> Conditional on missing a day of work due to unexpected illness, 28 percent of men and 44 percent of women are still not working 7 days later. A nontrivial fraction of the shocks continue even longer, especially for women: 31 percent of women are still not working 21 days after an unexpected illness, compared to 10 percent of men.

# **2.2 Summary Statistics**

Table 1 presents summary statistics of the working-age adults in the high frequency sample.<sup>8</sup> The sample is relatively young (an average age of 34 for men and 36 for women) and well educated by developing country standards: the average male has 11.2 years of education and the average female has 9.4 years of education. The typical household extends beyond a nuclear family; the average male is in a household with 5.6 total working-age adults and the average female is in a household with 6.1 working age adults. In Heath et al (2019) we show that the sample closely matches the characteristics of adults in urban Ghana surveyed in the Ghana Living Standards Survey conducted in 2012 and 2013.

Both male and female labor supply is high in this context: 72 percent of men and 66 percent of women report being employed at baseline (having steady work that they were doing regularly), and 65 percent of men and 56 percent of women worked in a given week over the

> 7 While these reports are suggestive of the typical length of an illness, these daily data are less suitable for precisely isolating illness shocks, given that we can identify illness only in days in which the individual was planning to work but did not.  That is, a series of several consecutive days off would only appear if each day after the original illness shock, the individual was planning to go back to work but still could not.  As a result, the rate at which respondents report seven consecutive days of illness shocks in the tri-weekly data (0.52% of weeks) is considerably lower than the rate at which they report a week of missed work due to illness in the weekly data (4.3% of weeks).  This result further supports our primary focus in the empirical analysis on the respondents surveyed weekly.

> 8 More than half (58%) of the respondents are female.  This does not appear to reflect differential response rates by gender in the high-frequency survey, since a very similar percentage (57%) of adults in the household roster for the 2013 Labor Force survey from which the sample was drawn are female. The Ghana Statistical Service (2014) also reports that the 2010 Population and Housing Census found more females than males in Accra.

11
estimates of the impact of CIT rate increase on employment, wage bill and gross revenue of the offshore sector are all null. If anything, we find small _increases_ in aggregate economic activity among manufacturing firms in the offshore sector, but the estimates are imprecise.

To explain the apparently inconsistent findings of a large fall in the number of entrants and no changes in aggregate activity, we turn to more granular data. First, we find that entrant firms are typically very small and that economic activity in the offshore sector is highly concentrated in a few, large incumbents remaining largely active in the postreform period. Second, the differences-in-differences analysis on a balanced firm-level panel shows that the CIT reform has no significant effects on the employment, wage bill and revenue of offshore incumbents.

Taken together, our results strongly reject the hypothesis that the increase in corporate income taxes led to a decrease in aggregate economic activity, or that they hampered the performance of firms subject to the CIT rate increase.

Like our paper, several other empirical contributions document a limited economic effect of CIT reform. Buba and Wong (2017) review the literature on SEZ and conclude that despite their ability to attract foreign investment and boost exports, their impacts on employment and spillovers to other local firms are unclear. Interviewing management from firms in SEZ across countries, Frick and Rodríguez-Pose (2023) document that factors such as infrastructure, labor costs and political stability are more important for investment than tax benefits. We add to this evidence by focusing on the specific role – of corporate income taxes in developing economies which is crucial given their typical – fiscal needs independently of other policy measures.

Beyond developing economies, survey evidence from small and medium enterprises (SMEs) often points to other barriers such as financial constraints and regulatory burden, as much more relevant to business decisions (Ravšelj et al., 2019; Wang, 2016). Gordon and Li (2009) conclude that the most important tax provision to encourage risk-taking by corporations is beneficial treatment of losses (e.g. allowing it to be deducted from payroll taxes), rather than lowering tax rates. Akcigit and Ates (2023) use an estimated general 4
Further work will also follow up with analyses of VOI when some degree of uncertainty always remains after a valuation study, touched upon at the end of section 4; this is the practically more relevant and interesting case. We conjecture that the VOI will be roughly inversely proportional to the remaining standard deviation of B; proofs are here clearly required.

A further issue needing follow-up work is to discuss more precise information about V, the resource opportunity value, which is here assumed uncertain for P, but certain for S. In practice, S is likely to be uncertain about V. The information about V for P could then be improved through similar valuation efforts to those studied for B. A more precise assessment of V is useful for P only when P is not fully altruistic, and S knows V for certain. When V is not known for certain by any party, additional work to find a more precise V value would be useful.

We finally mention that Appendix C studies related simulations assuming that the distributions of B and V are both log-normal (instead of normal). We find many simulation results to be similar. A major difference is that the probability of a “type 4” decision (not saving the resource when it ought to be saved) now is lower in all cases considered.

# **References**

Ades, A. E., Lu, G. and Claxton, K., 2004. Expected Value of Sample Information Calculations in Medical Decision Making. _Medical Decision Making_ , 24, 207-227.

Benthem, A. V. and Kerr, S. 2013. Scale and Transfers in International Emissions Offset Programs. _Journal of Public Economics_ , 107, 31-46.

Berger, J. O., 1985. _Statistical Decision Theory and Bayesian Analysis_ . New York: Springer.

- Bergland, O., 2005. Bayesian Estimation of Willingness-to-Pay from Contingent Valuation Data. Unpublished, Australian National University.

- Bergland, O., 2014. Benefit Transfer Without Apology. Unpublished, Department of Economics and Business, Norwegian University of Life Sciences.

Claxton, K., 1996. Bayesian Approaches to the Value of Information: Implications for the Regulation of New Pharmaceuticals. _Health Economics_ , 8, 269-274.

- Costello, C. J., S. Polasky, and A. Solow, 2001. Renewable Resource Management with Environmental Prediction. _Canadian Journal of Economics_ , 34, 196-211.

DeGroot, M. H., 1970. _Optimal Statistical Decisions_ . New York and London: McGraw-Hill.

Eckermann, S., and A. R. Willan, 2007. Expected Value of Information and Decision making in HTA. _Health Economics_ , 16, 195-209.

Eeckhoudt, L., A. Thomas, and N. Treich, 2011. Correlated Risks and the Value of Information. _Journal of Economics_ , 102, 77-87.

Gibbons, R., 1992. _Game Theory for Applied Economists_ . Princeton, N. J.: Princeton University Press.

25
20 export patterns has taken place since 1987.

**Table** 7: Ratio of CMEA Exporta to **OECD Exports, 1967-91**

||Czechostnvakia|Hungary|Poland|t.mania|Nemorandu<br>Standard<br>deviation|ts:<br> <br>CEE-3<br>|
|---|---|---|---|---|---|---|
|1987|2.20|1.18|0.82|0.95|0.54|1.33|
|1988|2.04|0.99|0.91|1.13|0.45|1.25|
|1989|1.73|0.78|0.81|1.06|0.38|1.06|
|1990|1.01|0.49|0.64|0.85|0.20|0.68|
|1991|0.56|0.41|0.51|0.58|0.07|0.49|

Source: IMF, Direction of Trade Stgtistics Yearbook, 1992.

Table 8 provides additional information relating to the switch from CMEA to OECD markets. It presents the annual changes in the value of exports of the CEE-3 and Romania in 1990 and 1991, as well as between 1987 and 1991 (the period over which the value of intra-CMEA exports was falling), to the FSU, Table 8: Changes in Value of CEE-4 Exports to FSUJ CEE-4. and OECD, 1990 and 1991 (million US S)

||Czec|hostovaki|a|Hu|ngary||Po|land|||Romania||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||1990|1991|TotaL<br>1988-91|1990|1991|Total<br>1988-91|1990|1991<br>|Total<br>1988-91|1990|1991|Total<br>1991-88|
|FSU<br>CEE-4<br>OECD<br>TOTAL|-1398<br>-745<br>661<br>-1481|<br>-898<br>-232<br>1685<br>556|-2910<br>-1007<br>2910<br>-1007|-482<br>-243<br>1152<br>427|194<br>-236<br>940<br>898|-1001<br>-598<br> <br>2856<br> <br>1257|78<br>498<br>2557<br>3133|335<br>-834<br>1110<br>611|1081<br> <br>-67<br>4845<br>5859|-1025<br>-632<br>-1097<br>-2754|<br>-572<br> <br>-310<br> <br>-387<br>-1269|-1309<br> <br>-1164<br> <br>-1791<br>-4264|
|Memor|andum: FSI|I:<br>Bala|nce of Tra|de|||||||||
|FSU:|-152|+1054||-442|-485||-1282|-1410||+687|-57||

Source: IMF, Direction of Trade Statistics Yearbook, 1992 to othcr European CMEA members, and to OECD countries (EC, EFTA, North America and Japan). Two points are worth noting. First, the increase in exports of the CEE-3 economies to the OECD more than offset the fail in exports to former CMEA markets.25 Second, there were significant differences in export performance among the CEE-5 economies. Poland stands out. Its exports to the FSU increased in both 1990 and 1991, while exports from other countries fell, and the annual increases in 1990 and 1991 followed expansion in both 1988 and 1989. The overall increase between 1987 and 1991 was slightly above US$1 billion. It should be noted that while the data on intra-CMEA trade until 1990 suffered from problems related A 25 Although the amounts offset each other, the terms of trade and budgetary implications are different. The collapse of intra-CMEA trade and the switch to world prices contributed to government budget deficits in the CEE-5, as a study on Hungary demonstrates (Abel, Hillman and Tanr, 1992).
# **9. References**

Andrade, E. B., & Ariely, D. (2009). The enduring impact of transient emotions on decision making. _Organizational Behavior and Human Decision Processes_ , _109_ (1), 1‐8.

Ariely, D., Loewenstein, G., & Prelec, D. (2003). “Coherent arbitrariness”: Stable demand curves without stable preferences. _The Quarterly Journal of Economics_ , _118_ (1), 73‐106.

Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost. _Organizational behavior and human decision processes_ , _35_ (1), 124‐140.

Ashraf, N., Fink, G., & Weil, D. N. (2010). _Evaluating the effects of large scale health interventions in developing countries: The zambian malaria initiative_ (No. w16069). National Bureau of Economic Research.

Ashraf, N., Karlan, D., & Yin, W. (2006). Tying Odysseus to the mast: Evidence from a commitment savings product in the Philippines. _The Quarterly Journal of Economics_ , _121_ (2), 635‐672 .

Bernard, T., S. Dercon, K. Orkin, and A. S. Taffesse. 2014. “The Future in Mind: Aspirations and Forward‐ Looking Behaviour in Rural Ethiopia.” Paper presented at Centre for the Study of African Economies conference on economic development in Africa, Oxford, UK, March 25 Bernard, T., S. Dercon, K. Orkin, and A. S. Taffesse. 2015. “Will Video Kill the Radio Star? Assessing the Potential of Targeted Exposure to Role Models through Video.” _The World Bank Economic Review_ , Volume 29, Issue suppl_1, 1 January 2015, Pages S226–S237 Berg, G and Zia, B (2017), “Harnessing Emotional Connections to Improve Financial Decisions: Evaluating the Impact of Financial Education in Mainstream Media”, _Journal of the European Economic Association_ 15(5): 1025–1055.

Berge, L. I., Bjorvatn, K., & Tungodden, B. (2011). Human and financial capital for microenterprise development: Evidence from a field and lab experiment. _NHH Dept. of Economics Discussion Paper_ , (1).

Bertrand, M., Karlan, D., Mullainathan, S., Shafir, E., & Zinman, J. (2010). What's advertising content worth? Evidence from a consumer credit marketing field experiment. _The Quarterly Journal of Economics_ , _125_ (1), 263‐306.

Bruhn, M., Legovini, A., & Zia, B. (2012). Financial Literacy for High School Students and Their Parents: Evidence from Brazil. _World Bank Working Paper_ .

Bruhn, M., Ibarra, G. L., & McKenzie, D. (2013). _Why is voluntary financial education so unpopular? Experimental evidence from Mexico_ (No. 6439). The World Bank.

Bruhn, M., & Zia, B. (2011). Stimulating managerial capital in emerging markets: The impact of business and financial literacy for young entrepreneurs. _World Bank Policy Research Working Paper Series, Vol_ .

Cardoso, A. R., & Verner, D. (2006). School drop‐out and push‐out factors in Brazil: The role of early parenthood, child labor, and poverty.

Cialdini, R. B., Trost, M. R., & Newsom, J. T. (1995). Preference for consistency: The development of a valid measure and the discovery of surprising behavioral implications. _Journal of Personality and Social Psychology_ , _69_ , 318‐318.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (1983). Applied multiple regression/correlation analysis for the behavioral sciences.

22
14 the sector shares in state capital construction investment from the first five year plan (1953-1957) to the sixth five year plan (1981-85). Despite the fact that more than three quarters of China's population derived their living from agriculture, it received less than 10 percent of state investment in the period 1953-1985. Meanwhile, forty-five percent of the investment budget went into heavy industry. Moreover, heavy industry received the lion's share of investment falling under the heading "other", including workers' housing and infrastructure. As a result, the value of the share represented by heavy industry in the combined total of agriculture and industry grew from 1 5 percent in 1952 to about 40 percent by the mid-1 970s (see Table 3).

Table 2:

**Sector Shares of State Capital** Construction **Investment**

|rive-Year<br>Plan|Agricult-ure|Light<br>Incustrv<br>(a)<br>;I)|Heavv<br>Industrv<br> <br>(e)|Other<br>(M)|
|---|---|---|---|---|
|First|7.1|6.4|36.2|50-3|
|Second|11.3|6.4|54.0|28.3|
|1963-1965|17.6|3.9|45.9|32.6|
|Third|10.7|4.4|51.1|33.8|
|Fourth|9.-8|5.8|49.6|34.8|
|Fifth|10.5|6.7|45.9|36.9|
|Sixth|5.1|6.9|38.5|49-5|
|1953-1985|8.9|6.2|45.0|39.9|

Source: State Statistical Bureau, Zhonaquo qudinczichantouzi tonaaiziliao (China Canital Construction Statistical Data 1950-1985), p.97.
<!-- Start of picture text --> Share of Informal Employees in the Labor Force vs. EPL Strictness<br>in European countries, 2004-2009<br>Eastern and Southern Europe Western and Northern Europe<br>GR<br>IE<br>IE<br>IE<br>PT UK<br>BG UA PT<br>UK UK<br>SK HUHUBGCZPLRURUEE LVITLVSISIEESILT ROES PT CH DK DK NLATAT NLNL NO FRFR<br>BE BE<br>HUSK EE FI DE SE<br>1.5 2 2.5 3 3.5 1 1.5 2 2.5 3<br>EPL strictness EPL strictness<br>East South West North<br>Fitted values, GR excluded Fitted values<br>Not included: Israel (EPL strictness 1.46, informal employees 25%)<br>Sources: Share of Informal Employees - calculation with ESS data<br>EPL strictness (version 2): OECD and Muravyev (2010)<br>.<br>Figure 1 Share of informal employees vs. EPL strictness<br>Share of Informal Employees in the Labor Force vs. Min Wage<br>in European countries, 2004-2009<br>Eastern and Southern Europe Western and Northern Europe<br>IL<br>IE<br>IE<br>GR GR<br>IE<br>UK<br>UA LV UA PT PT SI BG UK UK DK ATAT<br>RO E EEE ES SKPL PL ES ES HU CZITBGPTLVHULT SISI CH NODK NLNL NLFRFR<br>SK DE BE BE<br>EE HU FI SE<br>30 35 40 45 50 55 35 40 45 50<br>Minimum wage, Minimum wage,<br>% of average wage in industry & services % of average wage in industry & services<br>Countries without a min wage Countries with a min wage<br>Fitted values Countries without a min wage<br>Fitted, GR & IL excl. Fitted values<br>Some country labels are omitted<br>Not included: Russia (min wage 9% & 13%, informal employees 5% & 6%)<br>Not included: Cyprus (no min wage, informal employees 35% & 41%)<br>20 30<br>15<br>20<br>10<br>10<br>5<br>0 Informal employees, % of labor force 0<br>25 30<br>25<br>20<br>20<br>15<br>15<br>10<br>10<br>5<br>5<br>0 0<br>Informal employees, % of labor force<br><!-- End of picture text -->

**Figure 2 Share of informal employees vs. minimum wage level**

51
_Note: * A total of 189 participants (98 in the treatment group and 91 in the control group were interviewed in all 3 rounds)._ Source: Saraf, 2019; World Bank Group, 2018 This intra‐category analysis seems to suggest that low‐touch psychosocial intervention for entrepreneurs in FCV contexts might be most effective in cases of mild to moderate depression that may risk becoming chronic and severe distress in future. Such a diagnostic and preventative approach could result in significant health care cost savings, as well as improvements in business productivity.

# 6.2 Well‐Being

At the baseline, personal well‐being was high (with average WHO‐5 score of 80). Despite this strong starting point, there were substantial improvements observed in well‐being of SME entrepreneurs in the treatment group, especially 3 months after the intervention. Table 7 shows the ITT estimates of treatment effect on the WHO‐5 score at 5 weeks and 3 months post intervention, as well as results of analysis using pooled data. At the 3‐month mark, WHO‐5 score among entrepreneurs in the treatment group is 4.73 higher on average compared to their counterparts in the control group (Column 2). The difference between the scores is statistically significant at the 10 percent level (p=0.074). Using pooled regressions, WHO‐5 scores of entrepreneurs in the treatment group in 2.7 higher on average, though the effect is not statistically significant.

Table 7. Effect of Treatment on Well‐Being

||**(1)**|**(2)**|**(3)**|**(4)**|
|---|---|---|---|---|
||**ANC**<br>|**OVA**<br>|**P**<br>|**ooled**<br>|
||**5 weeks**<br>**WHO‐5 score**|**3 months**<br>**WHO‐5 score**|**Pooled**<br>**WHO‐5**<br>**score**|**Clustered SEs**<br>**WHO‐5 score**|
|Treatment|0.751|4.732*|2.710|2.710|
||(2.147)|(2.637)|(1.698)|(1.958)|
|Baseline score|0.442***|0.338***|0.392***|0.392***|
||(0.056)|(0.067)|(0.0436)|(0.0580)|
|Round‐ ERKF|0.105|3.669|1.924|1.924|
||(2.197)|(2.742)|(1.750)|(1.845)|
|Age|0.134|‐0.135|‐0.00123|‐0.00123|
||(0.103)|(0.125)|(0.0810)|(0.0926)|
|Education|‐0.735***|‐0.207|‐0.480**|‐0.480**|
||(0.265)|(0.327)|(0.210)|(0.212)|
|Constant|50.73***|60.76***|55.73***|55.73***|
||(6.711)|(8.144)|(5.280)|(6.675)|
|Observations|205|199|404|404|

_Note:_ Standard errors in parenthesis.

Column 4 shows results of pooled regression with standard errors clustered at the individual level *** p<0.01, ** p<0.05, * p<0.1 Source: Saraf, 2019; World Bank Group, 2018 20