rafmacalaba/datause-encoder-data huggingface dataset:
this effect will decline for values greater or less than X . We therefore also experiment with an instrument that is defined as the growth rate divided by the squared difference between the <u>g</u> distance D from the village to the nearest city and X , or ~~.~~ (D−X)<sup>2</sup> To test the plausibility of the various instrument specifications, we regress the share of the migrants from the village on each instrument described above, along with a full set of village dummies, and a full set of province-year dummy variables (Appendix Table A.8, columns 1-3). When using the contemporaneous growth rate, we use data from 1991 to 2003, and when we use lagged growth, we use data from 1993 to 2003. In the table, each cell represents a separate regression, and we list the numerator in the row (either contemporaneous or lagged GDP growth) and the denominator in the column. We find a significant relationship between the migrant share and the lagged GDP measure, but only when we control for distance either linearly or quadratically in the denominator. However, the F-statistics suggest that these would be very weak instruments and unlikely to be appropriate for estimating the second stage.

We next explore whether there is an optimal distance X from the village in which the employment signal would be strongest, as discussed above. We re-specify the denominator as (X−D)<sup>2</sup> , and we perform a grid search over possible values of D to find the strongest relationship between the share of migrants in the village workforce and the instrument. For both GDP growth and lagged GDP growth, we find a strongly significant relationship between the migrant share and the instrument for values of D centered around 100 km. As it is generally implausible that rural residents could commute this distance over the period under study, or even much more than 25 km, this finding makes intuitive sense. We thus use a value of D =100km in column 4 of Appendix Table A.8.

We find that the growth instrument has the strongest relationship with the share of migrants from the village when we use contemporaneous growth. The cluster robust F-statistic is 7.64, which is below 10, but stronger than in other specifications. While one might prefer this specification based on instrument strength, we had some expectation that migration should follow the previous year’s growth.

Thus, we first report the second stage result with no additional covariates and using lagged city GDP growth (Appendix Table A.9). When no additional control variables are included, the estimated coefficient is negative and significant at the 1 percent level (column 1). Perhaps most importantly, the point estimate (-2.12) is quite similar to the point estimate reported in Table 10 with no covariates (-2.50), and is within the range found when also controlling for additional covariates. From the perspective of demonstrating the validity of the quartic in years since IDs 53
perspective. We do so by investigating the following pairs of Sub-Saharan African countries: Madagascar – Mozambique, Uganda – Kenya, Senegal – Guinea, and Mali – Niger. The selected countries exhibit both important similarities, in particular countries of a pair, and marked differences, e.g. in child mortality reductions. To analyze and compare the determinants of child mortality, we estimate dicrete-time hazard models of survival for children under 5 for each country. The transmission channels are analyzed by regressions that link socio-economic variables, such as education, with so-called proximate child mortality determinants, for example birth spacing. In a final step, the hazard models are used to simulate the effects of expanding mother’s education on child mortality.

In contrast to the mixed findings of the previous literature, we find strong complementarities between mothers’ educational achievement and child mortality in most countries. While the direct effect of education in child mortality models is not particularly robust, we show that mothers’ schooling lifts important demand side constraints in terms of the use of health services: Children of mothers with primary education are much more likely to receive vaccines. This effect on the demand for health services is not the only positive effect of mothers’ education. Better educated mothers tend to have longer birth intervals, which again considerably increases the chances of child survival. For other MDG-related variables, e.g. wealth proxies and access to safe drinking water, we fail to detect significant effects on child mortality, a finding that may however to a large extent be related to data limitations.

Despite its importance, our simulations show that achieving universal primary education will not suffice to achieve the child mortality reduction targets, at least without other relevant conditions changing substantially. The comparison across countries suggests that there are important variations in the effectiveness of policies aimed at reducing child mortality. Since some countries, which have been successful in the past, seem to have used their policy space, for example by extending vaccination coverage, future reductions will be more difficult to attain. This is also the main reason why our simulation exercises yield a fairly pessimistic outlook for the prospects of achieving MDG4: Even an overly ambitious policy scenario that combines universal primary education with universal vaccination coverage and an elimination of short birth intervals falls short of the envisaged goals in seven out of eight of the country cases.

The paper first sets out the analytical framework for the study of child mortality determinants and briefly reviews existing empirical evidence from SSA. We then present the results of our empirical analysis. The empirical part of the paper starts with an outline of the 3
were almost fully offset by increases in self-employment earnings.

the randomized match between and we Finally, using training providers apprentices, show that trainer characteristics can have a causal effect on an apprentice’s labor market outcomes. In particular, we find that apprentices who trained with the most profitable trainers had greater total monthly earnings compared to their peers who trained with less profitable trainers. We also find similar patterns when apprentices trained with the most experienced trainers, or trainers with the largest wage bills (a proxy for the size and skill of their wage workforce). The magnitude of this increase in earnings more than offset the negative treatment effects of training on earnings for the full sample, suggesting that the effectiveness of training programs can be improved by carefully screening training providers.<sup>6</sup> We make two main contributions to the literature. First, we add to the very limited set of experimental studies of apprenticeship training in developing countries. There is a larger literature that evaluates vocational training programs as well as business training programs in these contexts. Overall, these studies find that training programs are generally ineffective (Blattman & Ralston, 2015; McKenzie & Woodruff, 2013). We are aware of only two recent randomized control trials on apprenticeships in Africa. Cho, Kalomba, Mobarak, and Orozco (2013) evaluate a three-month apprenticeship program in Malawi and find no improvements in labor market outcomes. The study was plagued by high attrition rates, however. Cr ́epon and Premand (2018) examine a formalized (or improved) apprenticeship training program in Cˆote d’Ivoire that included an inclassroom training component, a formal certification scheme, and a training wage (or subsidy) for apprentices. They also find limited improvements in labor market outcomes. Our study provides evidence on an existing traditional system of apprenticeships rather than on an improved or formalized system like those examined in the studies in Cˆote d’Ivoire and Malawi. Further, since the NAP does not offer training wages, it is arguably more cost-effective for the government.

Second, our study is among the very few that use two-sided randomization designs. We are aware of two studies that employ such a design: Cr ́epon and Premand (2018) and Alfonsi et al. (2017). Cr ́epon and Premand (2018) use their design to test whether receiving an apprentice through the randomization affected a firm’s subsequent apprenticeship hiring decisions. They find evidence of displacement within firms, such that firms that received apprentices through the program hired fewer apprentices through 6 This is consistent with evidence from a recent randomized control trial on training in which Alfonsi et al. (2017) argue that their training program was effective in part because they worked with the best trainers in the Ugandan capital city of Kampala.

4
- Navrud, S. and J. Strand (2013), _Valuing Global Public Goods: A European Delphi Stated Preference (SP) Survey of Population Willingness to Pay for Amazon Rainforest Preservation_ . Policy Research Working Paper no 6637, World Bank.

- OECD (2012), _Mortality Risk Valuation in Environment, Health and Transport Policies_ . Paris: Organisation for Economic Co-operation and Development.

- Rolfe, J. and J. Bennett (eds.) (2006), _Choice Modeling and the Transfer of Environmental Values._ Cheltenham, U.K.: Edward Elgar.

- Roman, H. A., J. K. Hammitt, T. L. Walsh, and D. M. Stieb (2012), Expert Elicitation of the Value per Statistical Life in an Air Pollution Context. _Risk Analysis_ , 32, 2133-2151.

- Rose, J.M., and M.C.J. Bliemer (2013), Sample Size Requirements for Stated Choice Experiments. _Transportation_ 40, 1021-1041.

- Sackman, H. (1975), _Delphi Critique: Expert Opinion, Forecasting and Group Process_ . Lexington, MA: D.C. Heath.

- Soares-Filho, B.S., D. Nepstad, L. Curran, E. Voll, G. Cwerqueira, R. A. Garcia, C. A. Ramos, A. Mcdonald, P. Lefebvre and P. Schlesinger (2006), Modeling Conservation in the Amazon Basin. _Nature_ , 440, 520-523.

- Tol, R. S. J. (2005), The Marginal Damage Costs of Carbon Dioxide Emissions: An Assessment of the Uncertainties. _Energy Policy_ , 33, 2064-2074.

- Tol, R. S. J. (2008), The Social Costs of Carbon: Trends, Outliers and Catastrophes. _Economics - The Open -Access, Open- Assessment  E-journal_ , Vol 2, August 12-2008 .

Weitzman, M. L. (2001), Gamma Discounting. _American Economic Review_ , 91, 260-271.

- World Bank (2014), _Economic Valuation of Changes in Amazon Forest Area. Project Document Covering Six Project Elements_ . Development Research Group, Environment and Energy Team, the World Bank, Washington D.C.

- Ziglio, E. (1996), The Delphi Method and its Contribution to Decision-Making. in Adler, M. and E. Ziglio (eds.), _Gazing into the Oracle: The Delphi Method and its Application to Social Policy and Public Health_ , London: Jessica Kingsley.

35
# **Integrating Seasonal Forecasts and Insurance for Adaptation among**

# **Subsistence Farmers: The Case of Malawi**

Daniel E. Osgood<sup>1</sup> , Pablo Suarez<sup>2</sup> *, James Hansen<sup>1</sup> , Miguel Carriquiry<sup>3</sup> and Ashok Mishra<sup>4</sup>

> 1 Columbia University, International Research Institute for Climate and Society. Email: deo@iri.columbia.org

> 2 International Institute for Applied Systems Analysis and Boston University Dept. of Geography and Environment

> 3 Iowa State University Center for Agricultural and Rural Development

> 4 Indian Institute of Technology Kharagpur Rural Development Centre
**Table 2. Valid Responses to MBDC Questions**

||**Obs.**|**Percents**|
|---|---|---|
|**Total valid responses**|218|98.65|
|**Total invalid responses**|3|1.35|
|**Always “definitely yes”**|0|0|
|**Always “probably yes”**|0|0|
|**Always “Not sure”**|1|0.45|
|**Always “probably no”**|1|0.45|
|**Always “definitely yes”**|0|0|
|**Negative answer at**<br>**price of zero**|1|0.45|
|**Positive answer at price**<br>**of 500 yuan **|0|0|
|**Total **|**221**|**100.00**|

**Table 3. Responses to the Likelihood Questions (%)**

|**Price**|**Definitely Not**|**Probably Not**|**Not sure**|**Probably Yes **|**Definitely Yes**|**Total **|
|---|---|---|---|---|---|---|
|0|0.000|0.000|0.000|0.459|99.541|100|
|3|1.835|1.376|0.459|5.046|91.284|100|
|5|11.927|5.505|4.128|13.761|64.679|100|
|10|33.028|5.046|7.339|16.972|37.615|100|
|15|51.835|5.505|12.385|13.761|16.514|100|
|20|65.596|9.174|5.963|10.092|9.174|100|
|25|76.606|5.505|7.339|4.587|5.963|100|
|30|83.028|2.752|7.339|2.752|4.128|100|
|40|87.615|5.046|2.294|2.752|2.294|100|
|50|91.284|2.752|3.211|1.376|1.376|100|
|60|93.119|0.917|4.128|0.917|0.917|100|
|70|94.037|0.917|4.128|0.000|0.917|100|
|80|94.495|0.917|3.670|0.000|0.917|100|
|90|94.495|1.835|2.752|0.000|0.917|100|
|100|96.789|0.917|1.376|0.000|0.917|100|
|150|98.165|1.376|0.459|0.000|0.000|100|
|200|98.165|1.376|0.459|0.000|0.000|100|
|250|98.624|0.917|0.459|0.000|0.000|100|
|300|99.083|0.917|0.000|0.000|0.000|100|
|350|99.541|0.459|0.000|0.000|0.000|100|
|400|99.541|0.459|0.000|0.000|0.000|100|
|450|99.541|0.459|0.000|0.000|0.000|100|
|500|99.541|0.459|0.000|0.000|0.000|100|
|**Total **|**76.865**|**2.373**|**2.952 **|**3.151 **|**14.659**|**100**|

21
# Table of Contents

|Introduction|2|
|---|---|
|Frequently used sources|2|
|Constructing quinquennial and single-year mortality rates|3|
|Model life tables|4|
|World Bank projections of mortality indicators|4|
|U.N. Population Division projections of mortality indicators|6|
|How good are current mortality estimates|7|
|References|9|
|Sub-Saharan Africa|10|
|North Africa|13|
|Latin America and the Caribbean|13|
|Northem America|16|
|South, East, and Southeast Asia and Oceania|17|
|Southwest Asia|19|
|Europe and USSR|21|
determine the value range of the property to be sold, calls upon the interagency commission to set the starting price of assets, decides on the transaction details (deposits, date of sale, bid collection locations, deadlines for bid submission, etc). The announcement is published in _Reforma_ bulletin, the official source of upcoming privatization transactions, which, unfortunately, is published in extremely small edition sizes and not easily obtained. RFPF has not heeded the advice of the World Bank and other donors to provide for a wider circulation of data on companies being privatized (for example, through postings on the Web or increasing the circulation of _Reforma_ ), citing its need to carry out intricate and sensitive pre-privatization consultations with potentially interested and qualified buyers, who are limited in number for a sector as complex as the coal sector.

# **PREPARATION OF THE COMPANY FOR PRIVATIZATION**

This section reviews various measures that are part of the preparation of a company for privatization, including activities of a procedural nature and activities of a political or consensus-building nature. In some cases, activities are described that are _not_ part of the pre-privatization process in Russia. They are included in this discussion because they are typical, if not constant, aspects of pre-privatization preparation of a company, and the Russian experience might suggest lessons of a positive or negative nature.

_“ ”_ _<u>Unreserving of Federal Shares</u>_ <u>. As explained above, as the Federal shares in</u> coal companies were “reserved”, before the shares can be made available for sale they must be “unreserved”. This necessarily leads to the involvement of Federal agencies other than MGI, whose authority to set policies for privatization extends to “unreserved” assets only.

_<u>Consolidation of Shares</u>_ <u>. Before an enterprise can be privatized, the State’s shares</u> in its subsidiary companies must be consolidated. As repeatedly demonstrated by the experience in Russia, this can be a legally complicated, politically difficult process that encompasses some of the basic challenges of privatization faced by any government, including the need to ensure transparency, equity in the distribution of shares, and the appropriate valuation of assets. As illustrated by the example in Box 1 below, “The Consolidation of a Russian Coal Company”, years could pass before the ownership and financial consolidation of a company were finalized. This was due partly to the delays inherent in the trust management period and the resistance to privatization on the national level, and partly to regional opposition. An example of the latter is the Federal Government’s decision to consolidate surface mines in Irkutsk, Chita and Buryat regions into the company Vostsibugol in 1992. Shares in one of the mines retained by the Irkutsk oblast administration in a form of trust management were finally transferred by the regional authorities to MGI for consolidation into Vostsibugol’s charter capital only in December 2000, in preparation for the announcement of the sale of all Federal shares in Vostsibugol.

13
By focusing on costs, this study contributes to the missing half of the conversation about the costs and benefits of microfinance. We measure the size of subsidies using proprietary data on 1,335 microfinance institutions between 2005 and 2009. The 930 institutions in the 2009 sample served 80.1 million borrowers globally.

We calculate that on average, subsidies amounted to $132 per borrower, but the distribution is highly skewed. The median microfinance institution used subsidies at a rate of just $26 per borrower, and no subsidy was used by the institution at the 25<sup>th</sup> percentile.

These data suggest that, for some institutions, even modest benefits could yield impressive cost-benefit ratios. At the same time, the data show that the subsidy is large for some institutions. Counter to expectations, the most heavily-subsidized group of borrowers are customers of the most commercialized institutions, with an average of $275 per borrower and median of $93. Customers of NGOs, which focus on the poorest customers and on women, receive far less subsidy: the median microfinance NGO used subsidy at a rate of $23 per borrower, and subsidy for the NGO at the 25<sup>th</sup> percentile was just $3 per borrower.<sup>3</sup> While most firms earn positive accounting profits, only a minority earn economic profit (which accounts fully for the opportunity costs of inputs). Accounting profit reflects an institution’s ability to cover its costs with its revenues, without accounting for implicit grants and subsidies. We find 67 percent of institutions were profitable on an accounting basis (weighted by the number of borrowers per institution; just 58 percent were profitable weighted by institutional

> 3 As a robustness check, we estimated these figures on a subset of the sample (814 institutions) for which we had complete data on every variable. Those results are very slightly lower than those reported below (the results from the balanced panel were so similar that we do not report them). With the balanced panel, we calculate that on average, subsidies amounted to $128 per borrower, with a median of $21 per borrower and again no subsidy at the 25<sup>th</sup> percentile. The average subsidy for commercial banks is $255 per borrower and median of $89. The median (non-profit) microfinance NGO used subsidy at a rate of $21 per borrower, and subsidy for the NGO at the 25<sup>th</sup> percentile was just $2 per borrower.

3
In total, 13 percent of the control group included in the endline sample took entrepreneurship training between graduation and the endline survey.

LATE estimates are local average treatment effects that capture the impact of the entrepreneurship track for the students who complied with their assignment to the treatment or the control group. LATE estimates are obtained by 2SLS by instrumenting actual completion of entrepreneurship training with randomized assignment to treatment. In a first step, we estimate the effect of randomized assignment on completion of entrepreneurship training : Where (Ui) is a dummy variable that takes the value of 1 for individuals having completed entrepreneurship training, independently of their assignment in the control and treatment group.<sup>14</sup> As per the information provided above, this variable takes the value of 1 for 71 percent of individuals in the treatment group, and 13 percent of individuals in the control group. β captures the estimated effect of randomized assignment on effective completion of entrepreneurship training.

In a second step, we estimate the following equation to obtain the local average treatment effects of entrepreneurship education that account for non-compliance: Where Û� is the predicted entrepreneurship training completion from equation (4). θ provides the estimates of the local average treatment effect, i.e. the estimated impact of effectively completing entrepreneurship training.

As we will further discuss below, and as would be expected, the results are highly consistent between the ITT and LATE estimates. As such, we mainly focus on discussing the ITT estimates since they are more directly policy-relevant in showing what is the overall effect of offering entrepreneurship education on the average applicant. Still, the LATE estimates are useful in checking that non-compliance does not affect the results, and in particular in checking that

> 14 For the treatment group, we define “completion of entrepreneurship training” or compliance as completing the business training and receiving coaching. For the control group, we define “completion of entrepreneurship training” as having taken any type of entrepreneurship training since graduation.

13
- In _Mofokate v Mofokate_ (2000)<sup>46</sup> , the High Court found that traditional marriages are best dealt with by customary courts, since the Matrimonial Causes Act does not apply to such marriages.

- In _S v Ntwayame_ (2008)<sup>47</sup> the appellants were charged in the customary court under the statutory offence of stock theft and attempted to get the proceedings moved to the magistrate’s court, so they could have legal representation in the proceedings. Despite provisions permitting the transferal of a case before a customary court to another court if requested, the Customary Appeal Court directed that the trial proceed before the customary court.

Aside from these institutional difficulties experienced in customary courts, as customary law is unwritten, there are also significant challenges in proving its rules of law. Traditionally, this was not thought of as a problem, since “the rules of customary law are supposed to be in the breast...of the elders, chiefs and headmen who man these courts”, but increasingly this is not the case.<sup>48</sup> The case of _Kweneg Land Board v Mathlo_ (1992)<sup>49</sup> illustrates the different understandings of customary law, and its development.<sup>50</sup> In this case the question faced by the Court of Appeal was whether a rule of customary law prohibiting the sale of traditional land by private individuals could have changed. The majority judgment viewed customary law as living, and adaptable to changing circumstances; while the dissenting judge found that there must be clear and satisfactory evidence of such a change.

While there has never been a codification or substantive legislative reform of customary law in Botswana, it has always developed in response to changing conditions. As early as the 1930s, chiefs began allocating land for housing and cultivation to unmarried women.<sup>51</sup> Another study describes customary court proceedings where an urban unmarried daughter, who had contributed “beyond ordinary female contribution”, was able to continue to remain in the ancestral house on the basis of her direct financial contribution.<sup>52</sup> A study in 2009 undertaken in _Tlokweng_ periurban area on the fringes of Gaborone found that the old practice of the eldest male son inheriting all property has fallen into disfavor. Instead parents now divide property among all siblings by writing a will that is publicly distributed before death.<sup>53</sup>

> 46 2000 (2) BLR 430 (High Court).

> 47 CLCLB-066-07 (2008) BWCA 37 (1 January 2008)

> 48 Id 182

> 49 1992 BLR

> 50 Fombad 2010

> 51 Schapera 1994

> 52 Griffiths 1998

> 53 Kalabamu 2009

10