rafmacalaba/data-use-mentions-extended huggingface dataset:
for the same destination country would yield inconsistent data. Priority is given to the foreign-born definition, and these data are always used if at least three censuses using that definition and with detailed bilateral information are available for a particular country. However, only nationality data are available for many destination countries. For countries such as Japan that rarely offer citizenship to foreigners, this does not pose much of a problem since foreign-born and nationality data will be very similar. For other destination countries, including data based on the nationality concept will lead to disparities. When fewer than three foreign born data sources are available and the nationality data are of superior quality, the nationality definition is chosen (see appendix 1). Where fewer than three data points by either definition are available, several assumptions are made to fill the missing data.

# _Missing Censuses and Census Data_

The final hurdle in constructing the global migration matrices is dealing with omitted data. No census round is truly complete since no round has ever included every country in existence at the time. Censuses are expensive because of their universal coverage and labor intensity. For those reasons, many countries have started to conduct censuses only recently (Bhutan began in 2005). Censuses can also be abandoned because of civil unrest or military conflict. They can also be politicized, because they can be used to estimate the size of a particular ethnic group. In other words, data may simply never be released even if they are collected. Nor is there any guarantee that a question on nationality or country of birth will even be included in the census questionnaire. Many countries in Central Asia, as well as Fiji, Sri Lanka, and Tonga, have in some years included questions on ethnicity instead, which is useless for identifying migrants. For all these reasons, inevitable gaps in the data emerge (see table 2).

Three conventions are adopted for constructing missing data. The one that is ultimately used depends on how many data are missing and for which decades these data are missing relative to
> are used to generate the welfare data. However, this step might entail an increase of noise in the ELL estimators.

Note that, if the model parameters were kept fixed to the initial survey estimates from step 1 (skipping step 2), the above ELL estimate _τ_ ˆ _c_<sup>_ELL_</sup> would be a basic Monte Carlo approximation to the marginal mean of the indicator, _E_ ( _τc_ ; _θ_<sup>ˆ</sup> 0), with respect to the distribution of the welfare (given the correlates) induced by the nested error model (1), with _θ_ replaced by the initial estimate _θ_<sup>ˆ</sup> 0. Note that _E_ ( _τc_ ; _θ_ ), evaluated at the true _θ_ = ( _β, ση_<sup>2</sup><sup>_, σ_</sup> _e_<sup>2),isunbiasedbydefinitionsinceitequalstheexpectationofthe</sup> indicator under the true model.<sup>9</sup> According to this, the prediction error of the ELL estimator can be decomposed as described in ELL (2003), where these sources of error are described as follows:

1. The **idiosyncratic error** is related to how the actual value of the expenditure for a given location, _c_ , deviates from its expected value due to unobserved aspects in the expenditure for the location (ELL, 2002). For locations with smaller population sizes, the underlying distribution is not likely approximated when errors are drawn. This, however, is related to the explanatory power of the independent variables in the model, the smaller the unexplained portion of the model, the smaller the idiosyncratic error. With poorly fitting models, estimates for locations with smaller populations are likely to suffer from more variability across simulations. Therefore, in order to minimize this error, one of the goals of the modeling stage is to obtain the highest possible _R_<sup>2</sup> .

>
.<sup>9</sup> In 2003/04, however, the measures to raise domestic revenue, coupled with across the board cuts in all expenditures, resulted in a dramatic fall in the SBI. Nonetheless, some views that it was the changes in the accounting practices that contributed to the SBI’s dramatic improvement. For example, since the 2007/08 Budget, operation and maintenance (O&M) spending is explicitly included in development expenditure (Bank of Botswana, 2006). Over time Botswana’s

**Figure 4.  Botswana: Sustainable Budget Index (SBI)**

<!-- Start of picture text -->
1.2<br>Introduction of SBI<br>1.1<br>1.0<br>0.9<br>0.8<br>0.7<br>0.6<br>0.5<br>Source: Author’s calculation based on data provided by the<br>authorities.<br><!-- End of picture text -->

development expenditure has become much less of capital expenditure, comprising a mix of capital and current spending, some with no discernable end in sight.<sup>10</sup> The more recent 40 percent expenditure rule has also helped discipline overall expenditure somewhat. Yet again, in 2008/09, barely three years after the introduction, total government expenditure exceeded 40 percent of GDP albeit marginally, caused by the sharp rise in development expenditure and the negative GDP growth affected by the slump in diamond sales (see below).

> 9 SACU revenue was exceptionally high during 1999/00-2000/01 because of the rapid depreciation of the South African Rand.

> 10 Consulting fees and HIV/AIDS treatment program are accounted as development expenditure, not as recurrent spending. However, such spending is not additional investment, and categorizing it as such can distort the objective of rebalancing the budget in favor
villages that we visited, we conducted a survey with the village chief in 714 villages (97%). Among the 180 villages that participated in the gender parity treatment and were visited, a total of 176 village chief surveys were conducted. We find no differences in attrition by treatment status.

# **Household Survey**

Per village, we targeted five randomly selected households. Within households we randomly selected the (adult) respondent in such a way as to ensure that each gender was represented equally within the sample. Given that 735 villages were visited, the study should make use of 3,675 6
invest plunged, as a result of weak economic prospects, particularly in advanced economies. Limited profit opportunities and high risk reduced new flows of investment, reinforcing the vicious cycles of excess capacity, low demand, and excess capacity.

The Chinese economy was hit hard by the global crisis, mainly through trade and capital flows. GDP of almost all of China’s main trade partners fell after the onset of the crisis in the fourth quarter of 2008. China’s volume of exports of goods and services declined 10 percent in 2008/09 (China Statistics Yearbook 2011). Market-based investment and confidence declined severely, 4
current account balance are positive and significant in regression [2] of Table 1, therefore, both fiscal and external savings play a role in limiting the adverse impacts of the pandemic on economic growth. Consequently, countries with smaller primary deficits or primary surpluses have space to finance policies that could help avoid deeper declines in economic growth. The same can be said about countries that have accumulated external savings (i.e. current account surpluses). Finally, the estimated coefficients of general government gross debt are negative but insignificant in most cases, and hence a country with larger general government gross debts could still face a significant decrease in economic growth.

The pandemic has adversely affected economic activity in all regions. Although economic growth declined significantly in Sub-Saharan Africa, this decline is smaller than the developing country average after controlling for an array of growth drivers (see Tables 1 to 3). Consequently, we test whether the different drivers of growth have a different impact in Sub-Saharan Africa vis-à-vis other developing countries in Table 3. We include interaction terms between the Sub-Saharan Africa dummy and selected explanatory variables —including, trade openness (level and composition by partner and product), gross capital inflows (level and composition by type of inflow), government response indicators, and health and human capital indicators. For most of the drivers, we are unable to find a significant coefficient for the interaction with SSA. Therefore, the average impact on growth for developing countries is similar to that for SSA countries. The only exception is gross capital inflows (as percentage of GDP), with a positive and significant interaction coefficient. This finding supports that the financing flow channel may be weaker in Sub-Saharan Africa when compared with other developing areas.

# **5.3 Instrumental Variables Estimation**

We conduct an in IV regression analysis to overcome endogeneity caused from a simple linear regression. The results from the 2020 human capital index (HCI) are positive and significant (i.e. 20.61 points in [2] in Table
prompting them to migrate. According to their view, migration, in turn, increased tensions and contributed to the outbreak of the civil war. Note, however, that there are sharp disagreements about this possible causal role in the Syrian civil war played by climate change via migration <mark>(Fröhlich,</mark> 2016; Selby et al., 2017) and that, more generally, the relationship between migration, climate change, and conflict is particularly complex and context-specific.

# _C. International versus internal migration_

Previous research paid more attention to weather- and climate-related international migration due to the paucity of internal migration data in developing contexts (Laczko and Aghazarm, 2009). However, the picture has changed in the last decade, as we are witnessing an increasing number of studies focusing on the relationship between weather shocks and short- or long-distance within-country movements, sometimes even comparing migration outcomes across multiple types of destinations. Gray and Mueller (2012b) study the effects of natural disasters in Bangladesh and find that these are stronger and more significant for local movements than long-distance outmigration. Jessoe, Manning, and Taylor (2018) show that extreme heat events in Mexico boost rural-urban internal migration as well as cross-border migration to the United States. Hirvonen (2016) finds that, in rural Tanzania, temperature increases reduce internal migration via increased liquidity constraints implied from the estimated negative consumption shock, but detects this effect only for men. Peri and Sasahara (2019), using a gridded global data set covering the period 1970-2000, find that progressive warming reduces rural-urban migration in poorer countries but increases it in middle-income countries. Gray and Bilsborrow (2013) find that adverse rainfall conditions reduce local, short-distance migration (i.e., moves within the same canton<sup>5</sup> ) and international migration in Ecuador, but increase internal long-distance (between-canton) migration, pointing to highly heterogeneous impacts concerning the type of migration. Nawrotzki, Riosmena, and Hunter (2013) find a positive and statistically
Inputs<br>Weather + FE Weather + FE<br>Weather Weather<br>0 2 4 6 8 10 12 14 16 18 0 2 4 6 8 10 12 14 16 18<br>Tanzania Uganda<br>p < 0.05 n.s. p < 0.05 p < 0.05 n.s. p < 0.05<br>.1 .1<br>.05 .05<br>0 0<br>-.05 -.05<br>* Weather Product * -.1 * Weather Product * -.1<br>MERRA-2 -.15 MERRA-2 -.15<br>ERA5 ERA5<br>CPC CPC<br>* Dep. Var. * * Dep. Var. *<br>Value Value<br>Quantity Quantity<br>* Model * * Model *<br>Weather + FE + Inputs Weather + FE + Inputs<br>Weather + FE Weather + FE<br>Weather Weather<br>0 2 4 6 8 10 12 14 16 18 0 2 4 6 8 10 12 14 16 18<br><!-- End of picture text --> _Note_ : The figure presents specification curves, where each panel represents a different country, with three different models presented within each panel. Each panel includes 18 regressions, where each column represents a single regression. Significant and non-significant coefficients are designated at the top of the figure. For each Earth observation product, we also designate the significance and sign of the coefficient with color: red represents coefficients which are negative and significant; white represents insignificant coefficients, regardless of sign; and blue represents coefficients which are positive and significant.

66
International Mathematics and Science Study (TIMSS) 2007 (I.V.S. Mullis et al. (2008)), only half of Indonesia‟s students performed above the lowest international benchmark. Hanushek (2008) also finds that just nearly 30 percent of a cohort of grade nine Indonesian students had achieved full literacy. Data on service quality suggest substantial scope for improvements in efficiency. Teacher absenteeism is estimated at 15 percent (SMERU (2008)).

Against this backdrop of national efforts at promoting education quality, the Government of Indonesia in 2002 instituted a decree that gave school committees a greater role in advising and supporting school management, and encouraged greater engagement with community.<sup>6</sup> The decree stipulated that school committees would replace existing school-level committees known as BP3 ( _badan pembantu penyelenggaraan pendidikan_ ) in Indonesian. The primary function of the BP3 was to raise funds from parents and the community to support the school, yet the funds were largely handed over to principals. The school committee would go a few steps further, making recommendations on school expenditures, teacher

> 5 Enrollment figures calculated using SUSENAS 2009. Enrollments dipped below 100 percent during the 1997-98 crisis, but returned to pre-crisis levels in the 2000s. 6 Lampiran I Keputusan Menteri Pendidikan Nasional,Nomor 044/U/2002, Tanggal 2 April 2002 5
to re-state here that using 5-year, non-overlapping panel data has the disadvantage of reducing the number of observations, and thus statistical power, substantially. In addition, the short-run relationship between the RRA and GDP growth is of substantial interest, too. By construction, 5- year panel data eliminates much of this short-run relationship. Nevertheless, we realize that it has been common practice in the growth literature to report estimates that are based on 5-year, nonoverlapping panels. These estimates should be viewed as complimentary to the distributed lag estimates that we reported in Table 11.

Thus, with the above in mind, it is gratifying that the estimates in Table 12 produce very similar results to the distributed lag estimates that are based on annual panel data. Controlling for country fixed effects as well as time (i.e. 5-year) fixed effects, Table 12 shows that increases in the absolute relative rate of assistance had a significant negative effect on GDP and consumption growth. Quantitatively, the estimates in columns (1) and (2) imply that, on average, a ten percentage point increase in the absolute relative rate of assistance reduced GDP growth over a 5-year period by around one percentage point; and consumption growth by around half a percentage point. Columns (3) and (4) document that this significant negative effect of increases in the absolute RRA on GDP and consumption growth continues to hold when excluding outliers. These fixed effects estimates, that are based on 5-year non-overlapping panel data, therefore reconfirm the main finding of our baseline analysis: distortions to the relative price between agricultural and non-agricultural products have had a significant negative GDP and consumption growth effect in Sub-Saharan African countries.

# **5.3 Effects on Sector Size, Agricultural Production, and Investment**

We now examine the effects that changes in the relative rate of assistance to agriculture had on the size of the agricultural sector, real agricultural output growth, and aggregate investment. To start off the discussion on these channels through which variations in the RRA have real
which focuses on changing mindsets (that is, <mark>developing positive outlook and resilience, and improving decision‐making abilities), may be incremental over time. It also implies t</mark> hat the impact of psychosocial interventions, in general, on mental health and well‐being may take a while to manifest, and impact evaluations need to factor that in.

Since this is one of the first studies looking at the impact of such an intervention on a non‐clinical population, a proper benchmark for comparison does not yet exist. For instance, it was not possible to answer how a reduced odds ratio of 0.46 of encountering depression and anxiety compares to other interventions for entrepreneurs. However, consultations with clinical psychologists in Pakistan and at the University of Liverpool who have conducted PM+ RCTs suggest that a reduction of this magnitude in the prevalence and intensity of depression and anxiety symptoms is meaningful for a non‐clinical population such as entrepreneurs. That the PM+E curriculum was able to move people across categories of depression and anxiety is also a test of clinical meaningfulness.

Given the challenging implementation environment, attrition levels were higher than anticipated which reduced the power to detect statistically significant impact with greater confidence. At the same time, with the existing sample size, the results show (clinically) meaningful and directionally expected results. Three months after the intervention, based on analysis of pooled data across two follow‐up rounds, entrepreneurs in the treatment group experienced statistically significant reduction in the intensity and prevalence of depression and anxiety symptoms and higher levels of well‐being compared with the control group. This implies that with a larger sample in future studies, these effects could be determined with greater confidence.

# 7. Conclusion

The project demonstrates that empirical research, including RCTs, can be conducted in challenging, FCV settings through appropriate rapid training of local researchers and NSPs. The ERKF project provided a unique setting for researchers to test the hypothesis that financial assistance, coupled with the 5‐week
Problem Loan Fund.

The data on bank ownership and major corporate events consists of hand-collected annual information primarily using the disclosed notes of the audited financial statements of banks and, only in some cases supplemented with news media reports and information from other IFIs for cross-checking. The ownership classification has been designed to reflect differences in bank operations that stem from shareholder profiles. There are 4 groups: foreign (state-owned and private) banks, local state-owned banks, local private banks, and PEP family-associated banks.<sup>q</sup> In general, for bank mergers, there are three important dates: (1) the announcement of possible transaction and application with the relevant authorities to receive their approval, (2) the closing of the transaction when ownership rights are transferred, and (3) the transfer of assets and liabilities. In our analysis, to identify a merger or acquisition, we consider the second date—that is, the closing of the transaction, while the date when the financials of the target institution are not compiled anymore is usually later. The bank financials during the transition period between the

> j <u>https://www.nationalbank.kz/file/download/72713.</u>

> k <u>https://www.nationalbank.kz/file/download/72716.</u>

> l <u>https://www.nationalbank.kz/file/download/72707.</u>

> m <u>https://sk.kz/investors/financial-performance/?lang=en.</u>

> n <u>https://www.nationalbank.kz/en/news/godovoy-otchet-nbk.</u> o <u>https://www.kfu.kz/index.php/ru/otchjotnost.</u>

> p <u>https://www.fpl.kz/en/audit</u
Industry Restructuring and Regulation -Building a base for sustainable growth

# _2.1. 1 Cross country studies_<sup>_9_</sup>

Investigating the impact of infrastructure on growth has long been hampered by the lack of available data. A recent study by Canning (1999) attempts to start to redress this by considering information from 152 countries from 1950 to 1995. Some of the more relevant findings from this study are presented below. While this is an important step forward, it does still contain a significant flaw. Only physical stocks of infrastructure are available; it is not possible to measure the quality of the service being derived from those stocks. This problem should be kept in mind when considering the results of this survey.

Canning was able to consider the impact of infrastructure on economic growth from the period 1970 to 1990 (this sub-sample was chosen to ensure a sufficiently large number of countries had continuous data series). The results, shown in Table I below, are suggestive of the impact of infrastructure on economic growth. A noteworthy result of the study is that telephone lines are a significant explanatory factor while electricity capacity has a negative impact. Without further investigation, it is possible to build plausible explanations as to why electricity capacity could have a negative impact, however, these would be purely speculative.'<sup>0</sup>

|_Variable_|_ModelI _|_Model 2_|**_MO_**|
|---|---|---|---|
|Constant|1.148<br>(3.45)|1.061<br>(0.77)|3.028<br>(4.31)|
|Log GDP per capita 1970|-0.211<br>(3.89)|-0.303<br>(1.92)|-0.449<br>(4.23)|
|Log education per worker<br>
- 22 -

In sum, the record suggests that by beginning with relatively small investments in formal institutions, and gradually increasing the complexity of development in terms of variety of modes supported and building management and policy bases, these countries were able to build incrementally from experience.

4. Responsive Planning: In general, these systems were planned in response to -- not in anticipation of -- employment demand. In early stages, manpower data and manpower forecasting capacity were largely absent. Investments were justified on the basis of demonstrated industrial expansion. The development of strong institutional linkages between training and employment to facilitate incremental and localized planning and adjustment were, in retrospect, important alternatives to formalized manpower forecasting. In this context, the location of training institutions became an important variable. In Korea sites were chosen to b2 close to expanding enterprises; in Brazil, mobile training units were created to take training to the trainees.

5. Early and Sustained Involvement of Enterprises: In all three countries sustained efforts were made to establish linkages between training and employment for all modes (in Brazil, these linkages had been part of the SENAI tradition since the 1940s). Enterprises played active roles in curriculum and enrollment decisions and in the design and provision of on-the-job training experience and apprenticeships. What may be most important is the consistency of commitment in training