rafmacalaba/datause-encoder-data huggingface dataset:
community wealth ranking exercises and low wages to target the program. In practice, the characteristics of participants may differ from the eligibility criteria because of differences in how local officials select beneficiaries and in the opportunity cost of participation. There are two types of targeting that may modulate impacts. The first is the selection of village-chosen beneficiaries. As noted above, some untreated households in our study were village-chosen beneficiaries. We examine the correlation between baseline per capita food consumption and participation of these households as an indication of whether the village selection procedures targeted poorer households. Our preferred measure of baseline food security comes from the IHS3, because unlike round 1 of the evaluation data, the IHS3 data were collected before the intervention was announced. We cannot assess targeting on short-term food security, because survey round 1 data were collected after the program was announced and may be affected by anticipated PWP earnings. However, if PWP is used locally in response to shortterm shocks, the lag between the IHS3 and program implementation may explain lack of correlation between time-varying characteristics such as food security and participation.

Nationally, Figure 3 illustrates that there is very little correlation between food security in 2010/2011 and participation through the village selection process. This may suggest that the village selection process either responds to short-term food security or relies on criteria that are orthogonal to long term consumption.<sup>15</sup> As shown in Figure 4, the relationship between food security and PWP participation varies by region. In the North and Central regions, participation of untreated households was uniform across the distribution of baseline food consumption.<sup>16</sup> In the South, households with lower baseline food consumption were if anything _less_ likely to be chosen by GVH and participate in PWP.

The second type of targeting is self-targeting, captured by participation by randomlyselected households from different points of the distribution of baseline food consumption. This mimics an unrationed PWP like NREGA. Among treated households, the correlation between accepting PWP work and IHS3 food consumption is negative in the North (indicating pro-poor targeting and self-selection of the poorest households), but not in the Central or Southern regions. Though self-targeting seems more prevalent in the North, there is no evidence of displacement of work in the market for casual wage labor (“ganyu”) in any region.

Overall, Malawi’s PWP is rationed and not targeted towards the food-insecure. Mistargeting could explain the lack of improvement in food security if the program employed people

> 15The autocorrelation between log per capita food consumption in the IHS3 and survey round 1 in control villages 0.30. Over shorter horizons, between any two adjacent survey rounds, the autocorrelation in control villages is close to 0.5.

> 16Food consumption data from the IHS3, accounting for seasonality by detrending by week-of-interview.

22
neighborhood (Figure 1). These results corroborate the idea that not only perceptions of criminal incidents but also actual knowledge of members of the community having been victimized is very low. These results are almost exactly corroborated by all 32 focus groups held in different parts of the country. Interestingly, the incidence of politically motivated violence seems to be higher especially in urban areas.

<!-- Start of picture text --> Figure 1: Bangladesh: Very high perception of harmony in the community<br>Source: World Bank Gender Norms Survey 2006 - respondents sayingpeople in<br>their locality live in harmony v/s fight a lot<br>100<br>90<br>80<br>70<br>60<br>Rural<br>50 Urban<br>40<br>30<br>20<br>10<br>0<br>Men 25-50 Women 15-25 Women 45-60 Community Total<br>Leaders<br>%<br><!-- End of picture text --> Less than 13 percent of the respondents had heard of any violent incident in the community<sup>4</sup> in the last year. At the bivariate level (table 1), residents of Chittagong and Khulna had a much higher probability of reporting such incidents in their community and this was driven to a large extent by politically motivated violence. The multivariate analysis, controlling for a range of individual and household characteristics including wealth quintile, land holding size and geographical area corroborates the bivariate results<sup>5</sup> . Essentially, region of residence and exposure to the media really determines whether you have heard of violent incidents in the last year. This commonsensical conclusion is nonetheless illuminating. What it says to us is that no other characteristic of the household such as poverty level (although individuals in the second quintile are slightly more likely to report knowledge of violence), landownership or religion or characteristics of the individual such as education or age are correlated with heightened knowledge of violence. On the other hand, residence in an urban area or in Khulna or Chittagong increases the probability of reporting knowledge of violence in the community. By contrast, living in Sylhet reduces that probability. Listening to the radio regularly also seems to make people more aware and they tend to report higher levels of knowledge of community violence.

> 4 Violent incident implies any one of the following – anyone‘s money was taken away or anyone assaulted outside the home or anyone encountered harassment while traveling or people physically hurt for political reasons.  The question does not include violence within the family

> 5 Annex 2

4
These econometric results are consistent with and support what was described in the previous figures and tables. Further, it is important to observe differences across services in terms of the importance of globalization on performance. Indeed, the results suggest that there are differential impacts of globalization on city performance, depending on the options city residents have for exit or choice. In the services where they can exit, such as water and electricity, then globalization has limited impact on city performance. In cases where they cannot exit, there seems to be more impact. The role of voice and participation, when you cannot exit seems to be critical, and significant, as shown by the significance of the variables such as bribery in utility and control of corruption (see Table 4 above).

Lee and Anas (1996) potently gave an illustration consistent with these results. They analyzed the decisions firms made to locate or not in cities in Nigeria and Indonesia, and also found that where public supply of electricity was unreliable, they could substitute by private generation capacity that they themselves installed. A sister paper (Kaufmann, Léautier, and Mastruzzi, 2004) provides a more detailed look at both the issue of technology and that of scale and city characteristics.

Country globalization (Kearney Globalization Index) also matters for city level performance. It is significant for all service variables except access to electricity, sewerage and telephone lines. What is interesting in the results in Table 4 is that city performance for network infrastructure (electricity grid, sewerage, telephone lines) is impacted by two aspects of governance (bribery in utility at the city level, control of corruption at the country level) and per capita income. Rich countries can afford to provide network infrastructure in cities. And better control of city and country level corruption leads to better performance of cities in providing access to services.

In summary, we find that there is an effect of city globalization on performance of cities using both the Taylor and the UN databases. While the strength of the effects appears to be somewhat more robust for governance variables than for globalization, it is present for the latter.

# **5 Determinants of City Governance**

## **5.1 A simple Framework**

The dramatic increase in empirical work on governance over the past few years has spearheaded a more in-depth analysis of the manifestations, causes, and consequences of misgovernance and corruption. It has drawn from cross-country data as well as in-country diagnostic perspectives. Significant inroads have been made in unbundling governance to measure and analyze its detailed components, as well as in exploring empirically the governance performance of different institutions—such as parliament, police, and customs.

We use three indicators of governance to investigate the relationship between globalization and governance. The first is an indicator of governance from the political perspective which we represent by an indicator of low illegal party financing. The second is a measure 26
we find with the double difference estimates. On the supply side, different distortions of the social assistance system such as a lack of transparency in the selection mechanism of beneficiaries or the use of categorical selection criteria resulted in distorted targeting. Targeting the non poor, in turn, may have had negative behavioral effects in terms of labor supply which could explain foregone income opportunities for those non poor who participated to the social assistance program. These problems may also have increased in weight during the period considered given that the volume of benefits increased without real restructuring of the targeting system. A second set of explanations may relate to the demand side through the mechanism of self-selection of beneficiaries. With the double difference procedure we compared two similar groups selected on the basis of observed characteristics. However, unobserved characteristics such as individual abilities may play an important role. It may be that the group of non beneficiaries is also the group with better individual abilities and which was able to better exploit the emerging growth opportunities. This problem is not really addressed by the matching procedure and the double difference estimates and motivated the panel approach that followed.

Panel survey estimates did not evidence any consistent significance of social assistance benefits in explaining welfare or poverty and pointed instead toward a strong growth effect. Therefore, even when we take into account unobserved heterogeneity, social assistance benefits do not seem to explain poverty reduction. We can conclude that the real engine of poverty reduction in Moldova between 2001 and 2004 has been growth and that social assistance has had either a negative effect through a displacement effect (social assistance beneficiaries who would have done better without benefits) or a non significant role.

# **References**

Abadie, Alberto, Drukker, David, Leber Herr, Jane and Imbens, Guido, 2001. Implementing Matching Estimators for Average Treatment Effects in Stata. _The Stata Journal_ , _1, pp. 1-18_ .

Abadie, Alberto and Imbens, Guido, 2002. Simple and Bias-Corrected Matching Estimators for Average Treatment Effects. _NBER Technical Working Paper No. 283_ Abadie, Alberto and Imbens, Guido, 2006. Large Sample Properties of Matching Estimators for Average Treatment Effects. _Econometrica 74, 1, 235-267_ Duflo, Esther, 2001. Schooling and labor market consequences of school construction in Indonesia: Evidence from an unusual policy experiment. _The American Economic Review 91, 4, 795-813_ .

Government of Moldova, 2001. Social Report 2001. Ministry of Labor and Social Protection. _Mimeo_ .

16
Data on the geographic dispersion of food prices in Russia in the eight months following price liberalization of January 1992 suggest the following:

- a. The volume of food sold in monitored shops increased substantially in the weeks following liberalization;

- b. The geographic dispersion of prices decreased significantly over time, suggesting some response of economic agents to the large price differences and opportunities for arbitrage;

- c. M,;re of the reduction in price dispersion took place in the period immediateiy following liberalization than in the subsequent six months;

- d. Although price dispersion declined over time, the decline was slower than would be expected if well-developed markets were actually functioning;

- e. Much (about two-thirds) of the remaining price distortion cannot be explained by traditional economic variables that we have, such as income and proxies for transportation cost.

Further development of food markets will require retention and deepening of price liberalization through removal of local controls and initiation of reform at the enterprise level, through privatization, demonopolization and new entry.

net profit. This amounts to 300 x 19 = 5700 rubles net profit on an investment of 300 x _5_ = 1500 rubles.

30
# **XII.   Conclusions**

In recent decades the MBA degree (or equivalent) has become an international degree. Internationally, far more students are receiving graduate business degrees, and competition between business schools and business students is assumed to have driven up the standard of graduate business education. But so far this has only been assumed and almost no work has been done to determine the perceptions of managers in developing country firms about the quality of the business school graduates produced locally.

In order to get a sense of the quality of MBAs throughout the world, the IFC used its extensive contacts to conduct a survey of developing country firms. The survey only covered firms with which the IFC had contacts, which may bias the results since these firms are usually the larger, well-established firms in developing countries. But even bearing this in mind, the results from the survey were extremely revealing.

The strengths and weaknesses of developing and transition country MBAs seem to overlap with those of MBAs from the U.S.: managers in the U.S. and in the developing countries find that the technical and analytical skills of MBAs are well developed while the practical training/skills and communication/language skills of MBAs are significantly lacking. This is an important result because it shows the areas in which MBA programs worldwide need to be strengthened.

In particular, the technical skills of developing-country MBAs were found to be strong, though Africa, South Asia, and the Middle East stood out because of the inadequate technical training of local MBAs. The communication skills were also considered strong, except in the Middle East, while the language skills seem to be a major problem for the Latin American and East Asian regions.

On the whole, only the African and Middle Eastern firms were significantly dissatisfied with the quality of local MBA graduates. It is interesting to note that these two regions also stand out because a significant percentage of firms from each of these regions said that there was a lack of availability of MBA graduates. So while the other regions had problems with certain skills of local MBA graduates (South Asia’s concern with analytical skills and Latin America and East Asia’s concern with language skills), the two regions with the greatest shortage of MBAs were producing the weakest candidates.

The results show that MBAs worldwide are not fully satisfying the needs of firms. The Eastern European region stands out as the region in which firms are the most satisfied with different aspects of MBA training. Each of the other regions of the world has its own particular weaknesses, while at the same time some common weaknesses (such as work experience and communication skills) stand out. These results show that a ‘cookie-cutter’ approach to training MBAs cannot work. Rather, MBA programs have to be tailored to suit the needs of the local business community while also teaching common business fundamentals. If not, East Asian and Latin American MBAs will still lack language skills, South Asian and African MBAs will 33
psychological tools can be extremely effective, in contrast to the skepticism often expressed about standard business training programs (McKenzie, 2021).

Personal initiative training seems to have particularly effective long-term impacts for men, especially in the upper quantiles of treatment effects. The reduced long-term impact for women entrepreneurs was a surprise to us in light of the positive 2-year impacts, and suggests a need to test whether complimentary interventions alongside personal initiative training are needed for them (such as helping them change industries, facilitating access to capital, or empowerment efforts). But even with these much smaller long-term impacts, the training still yields higher benefits for women than the cost of the training.

# **References**

Agte, Patrick, Arielle Bernhardt, Erica Field, Rohini Pande, and Natalia Rigol (2022) “Investing in the Next Generation: The Long-Run Impacts of a Liquidity Shock”, NBER Working Paper no. 29816 Balboni, Clare, Oriana Bandiera, Robin Burgess, Maitreesh Ghatak, and Anton Heil (2022) “Why Do People Stay Poor?” _Quarterly Journal of Economics_ 137 (2): 785–844.

Barker, Nathan, Dean Karlan, Christopher Udry, and Kelsey Wright (2024) “The Fading Treatment Effects of a Multifaceted Asset-Transfer Program in Ethiopia”, _American Economic Review: Insights_ 6(2): 277–294 Bernhardt, Arielle, Erica Field, Rohini Pande and Natalia Rigol (2019) “Household Matters: Revisiting the Returns to Capital among Female Entrepreneurs”, _American Economic Review: Insights_ 1(2): 141-60.

Blattman, Christopher, Stefan Dercon and Nathan Fiala (2022) “Impacts of industrial and entrepreneurial jobs on youth: 5-year experimental evidence on factory job offers and cash grants in Ethiopia”, _Journal of Development Economics_ 156: 102807 Blattman, Christopher, Nathan Fiala, and Sebastian Martinez (2020) “The Long-Term Impacts of Grants on Poverty: Nine-Year Evidence from Uganda’s Youth Opportunities Program.” _American Economic Review: Insights_ 2(3): 287–304.

Bloom, Nicholas, Aprajit Mahajan, David McKenzie and John Roberts (2020) “Do Management Interventions Last? Evidence from India”, _American Economic Journal: Applied Economics_ 12(2): 198-219.

Blume, Brian, J. Kevin Ford, Timothy Baldwin and Jason Huang (2010) “Transfer of Training: A Meta-Analytic Review”, _Journal of Management_ 36(4): 1065-1105.

16
||**2020**|**2021**|**2022**|**2023**|**2024**|**2025**|**2026**|**2027**|**2028**|**2029**|**2030**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**Energy**|0.00|2.13|4.27|6.45|8.61|10.73|12.92|15.06|9.06|11.26|13.39|
|**Constr**<br>**uction**|0.00|10.00|10.00|5.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Trade**|-0.01|-4.13|-10.36|-17.80|-25.16|-31.35|-37.75|-44.01|-26.47|-32.90|-39.13|
|**Accom**<br>**modat**<br>**ion**<br>**and**<br>**Food**<br>**Servic**|0.00|0.95|1.69|2.36|3.01|3.75|4.52|5.27|3.17|3.94|4.68|
|**es**||||||||||||
|**Transp**<br>**ortatio**|0.00|5.12|6.13|5.09|4.05|5.05|6.08|7.09|4.26|5.30|6.30|
|**n**||||||||||||
|**Bankin**|0.00|0.80|0.80|0.40|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**g-**<br>**Financ**||||||||||||
|**ing**||||||||||||
|**Real**<br>**Estate**|0.00|1.20|1.20|0.60|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Public**<br>**Admin**<br>**istrati**|0.00|0.20|0.20|0.10|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**on**||||||||||||
|**Educat**<br>**ion**|0.00|0.38|0.75|1.14|1.52|1.90|2.28|2.66|1.60|1.99|2.37|
|**Health**|0.00|0.43|0.86|1.31|1.74|2.17|2.62|3.05|1.84|2.28|2.71|
|**Other**<br>**Servic**<br>**es**|0.00|1.33|2.67|4.03|5.38|6.70|8.07|9.41|5.66|7.04|8.37|

_Table B. 9. Annual spending associated with investments and households’ consumption under the Virtual Net Billing Measure relative to the Reference Scenario by sector of economic activity for the period 2020-2030 (in million euros)_

||**2020**|**2021**|**2022**|**2023**|**2024**|**2025**|**2026**|**2027**|**2028**|**2029**|**2030**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**Agricul**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**ture**||||||||||||
|**Forest**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**ry**||||||||||||
|**Mining**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Food**<br>**Manuf**<br>**acturi**<br>**ng**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Textile**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Wood**<br>**and**<br>**Paper**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|

43
12 year between 1990 and 1993, with most of them losing over 30% of their sales between 1990 and 1991 alone. The labor market story is even starker, with nearly all state and a majority of privatized firms losing employment over the entire sample period. It is a telling indication of the magnitude of the transition effect that even the few state firms with _growing_ revenues had to decrease employment during the first four years of the transition to reduce the endemic overmanning of the old socialist enterprises.

**Figure 1**

# Decline and growth of firms in transition

<!-- Start of picture text -->
-0OFOETION  OFFPlUMS-1  DI$IECLINING  REVENUES  550-AN RATES OF REVENUE DECLINE<br>OF F RMS WITH  DECLINING  RtEVENUIES<br>100]  94_<br>80~~~~~8<br>SO  ElS4  rL  '-20 *  -21  :<br>40 ,20  l  10  4  - 36  _<br>t990-91  1991-92  1:92-93  1990-91  1991-92  1992-93<br>i  '  2  Nepwe[  _  t  _  *_  P 1 _  _ [] Ndn__st7d<br>PROPORTION  OF FIRU6  WI¢TH bECLINING  EMPLOYMENT  PROPORTION OF  FIRMS  WITH EMPLOYMENT  INCREASES<br>0ETWEEN  INITIAL  AN0  EN.O..  YEAR<br>sao  79<br>40 20  2  W  055.  aRe  -1  - 5<br>20  _  _  _  _  _  ~Pvtzd-  _  1  911 L  i, tle:9<br>1990-91  1891.92  1992-93  0  20  40  50  so  100<br><!-- End of picture text -->

But if Figure 1 shows the strength of the transition effect, it also offers a glimpse into the power of the privatization effect. The percentage of privatized firms losing revenues in each of the sample years is considerably lower than the percentage of state firms; among revenue-losers, privatized firms tend to arrest the decline markedly faster than state firms; and nearly half of privatized firms managed to create new employment over the entire period.<sup>27</sup> It might be objected that our results are skewed by a possible survival (exit) bias, since there may be more liquidations among privatized fums. There is no evidence, however, that this is the case; there have been many closures of state finrns under state enterprise laws (particularly in Poland) and relatively few closures (as opposed to reorganizations) of mid-sized and large state or privatized finns under bankruptcy laws in the three countries (Balcerowicz, Gray and Hashi, 1997). It is also worth noting that had such a bias toward the exit of non-viable private firms existed, it would have