rafmacalaba/data-use-mentions-extended huggingface dataset:
Table D4: ANCOVA Regressions by Urban/Rural [Dependent Variable: Food Insecurity] <!-- Start of picture text --> Fractional Index 3 Fractional Index 4<br>Ethiopia Malawi Ethiopia Malawi<br>-1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1<br>Effect on Food Insecurity Effect on Food Insecurity Effect on Food Insecurity Effect on Food Insecurity<br>Nigeria Nigeria<br>-1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1<br>Effect on Food Insecurity Effect on Food Insecurity<br>Mild Moderate Severe Index Mild Moderate Severe Index<br>HHI 1 HHI 2<br>Ethiopia Malawi Ethiopia Malawi<br>-1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1 -1 -.8 -.6 -.4 -.2 0 .2 .4 .6 .8 1<br>Effect on Food Insecurity Effect on Food Insecurity Effect on Food Insecurity Effect on Food Insecurity<br>Nigeria Nigeria<br>-1 -.8 -.6
well as ―second-order‖ effects such as improved nutritional intake, which improves workers‘ productivity. Similarly, Self and Grabowksi (2007) established a positive relation between different measures of agricultural productivity and average growth of real GDP per capita over 1960 – 1995 for a cross-section of countries. However, on the basis of panel data from 52 developing countries during 1980-2001, Gardner (2005) concluded that agriculture does not seem to be a primary force behind growth in national GDP per capita.

The recent empirical literature considers that the effect of agricultural progress on poverty alleviation is highly positive. Mellor (2001) goes as far as arguing that it is not economic 9
_Yij_ 2014 _− Yij_ 2000 and zero for _△Yij_ 2000 = _Yij_ 2000 _− Yij_ 1990.<sup>17</sup> The focus of the analysis is on the coefficient of the triple interaction term, i.e., _π_ 7. For night-lights, we can separate out the effects of the war years from that of the post-war years; the specification includes a dummy for war years [2002-2007] and another dummy for post-war years [2008-2011]. The omitted category is the pre-war years in this case. The error term _εijt_ could be spatially correlated. To correct for possible spatial correlations, we cluster standard errors at the route level.

The outcome variable _Yijt_ is expressed in shares for employment, built-up density, and skilled labor, and in logarithms for night-light luminosity. The dependent variables are differenced to wipe out the effects of time-invariant location heterogeneity. This is especially important in our analysis; for example, the labor-share in agriculture in a commune would be determined in part by the land quality and agro-ecological conditions. Part of the differences in employment shares observed between the Abidjan and non-Abidjan routes may be driven by these differences in agricultural endowment rather than the trade cost shock to the Abidjan route. For built-up density and skilled labor, the initial level of agglomeration economies may play a role in addition to the sunk investments in creating significant differences between the Abidjan and non-Abidjan routes. To address this concern, we include population density in 1975 as a measure of initial agglomeration economies in a commune/department. The DID regressions condition on a vector of pre-war locational attributes _Zij_ 0 which includes log of arc distance to the nearest route, a dummy indicating if the communes are from Mali, in addition to log of population density in 1975.<sup>18</sup>

# **(6.2) Defining Market Access**

Many studies rely on the distance to the nearest city/town as a measure of market access. It seems intuitive in the context of the
for the health and nutrition welfare index. Indeed, they seem to have comparable power in targeting chronically malnourished children.

**Table 2. Correlations between HAZ-score and alternative measures of well-being**

||Predicted income|Asset index|
|---|---|---|
|Area under ROC curve|0.6087<br>**0.6521**|0.6002<br>**0.6415**|
|k li|0.2133|0.1879|
|Spearman ran correaton|**0.2606**|**0.2230**|

Source: Own computations using HLCS 2001 and DHS 2000 (2005 in bold) In a last analysis of correspondence between welfare indices, we use the methodology proposed by Sahn and Stifel (2003). In order to assess the explanatory power of the asset index and the predicted income in predicting well-being, separate models of health and nutritional status are estimated conditioned on (i) the log of predicted per capita household income, (ii) the log of household asset index, (iii) both the log of predicted per capital household income and the log of household asset index. The probit regression model is fitted using an indicator whose value is one when the child is malnourished (HAZ-score under -2) and zero otherwise. Once the models are run, we use them to predict child HAZscores and compare the rank correlations and ROC curves between the fitted nutritional outcomes and the actual measured outcomes.

**Table 3. Probit estimates**

|HAZ-score<br>Predicte<br>onl|d income<br>y (i)|Asset<br>only|index<br> (ii)<br>Predict|ed income & Asset in|dex (iii)|
|---|---|---|---|---|---|
|Elasticity<br>
# **References:**

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- Abadie, A. and G.W. Imbens (2005) “Large Sample Properties Of Matching Estimators For Average Treatment Effects”, forthcoming, _Econometrica._

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- Borjas, George J. (1987) “Self-selection and The Earnings Of Immigrants”, _American Economic Review_ 77(4): 531-53.

- Chiquiar, D. and G. Hanson (2005) “International Migration, Self-Selection, and the Distribution of Wages: Evidence from Mexico and the United States”, _Journal of Political Economy_ 113(2): 239-81.

- Clark, X., T.J. Hatton and J.G. Williamson (2002) “Where do U.S. Immigrants come from and why?”, _NBER Working Paper 8998._

- Deaton, A. (1997) _The Analysis of Household Surveys: A Microeconometric Approach to Development Policy_ , Johns Hopkins University Press, Washington DC.

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., Tang, Q., Vernon, C., Leng, G., Liu, Y., Döll, P., Eisner, S., Gerten, D., Hanasaki, N., Wada, Y., 2018. Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns. Hydrol. Earth Syst. Sci. 22, 2117–2133. https://doi.org/10.5194/hess-22-2117-2018.

- IEA, IRENA, UNSD, World Bank, WHO. 2024. Tracking SDG 7: The Energy Progress Report. World Bank, Washington DC. World Bank. https://trackingsdg7.esmap.org/data/files/download-documents/sdg7-report2024-0611-v9-highresforweb.pdf. Accessed 06 Sept 2024.

- Institute for Health Metrics and Evaluation (IHME), 2020. LMIC Drinking Water and Sanitation Access Geospatial Estimates 2000-2017. https://cloud.ihme.washington.edu/s/bkH2X2tFQMejMxy?path=%2F. Accessed 15 Dec 2022.

- Khan, A. M., & Rodella, A. S., 2021. A Hard Rain's a-Gonna Fall?: New Insights on Water Security and Fragility in the Sahel. The World Bank. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/693481634066645154/a-hard-rains-a-gonna-fallnew-insights-on-water-security-and-fragility-in-the-sahel. Accessed 06 Sept 2024.

- Kukal, M. S., & Irmak, S., 2019. Irrigation-limited yield gaps: trends and variability in the United States post-1950. Environmental Research Communications, 1(6), 061005.

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- MacDonald, A. M., Bonsor, H. C., Dochartaigh, B. É. Ó., Taylor, R.
We examine more than 1,200 estimates of agglomeration elasticities from 70 studies covering 33 countries over the period 1973 to 2020. While raw agglomeration elasticities are positive and high in China, India and countries in Africa, countries such as Chile have negative elasticity estimates. Overall, raw estimates tend to suggest that developing countries reap huge benefits from urban density, nearly 5 points higher than developed countries. Further, these estimates are not driven by reverse causality.

These aggregate estimates, however, hide substantial heterogeneity. The differences in estimates can be attributed to estimation set-up (outcome and agglomeration measure), consideration of urban costs in estimating net benefits, and the variation in pay-off across sectors and skills. Studies using wages as an outcome variable have higher estimated elasticities compared to those using TFP measures, while studies using population size or density have larger estimates relative to market access measures. Service sector estimates are on average higher than manufacturing, while skilled workers disproportionately benefit from density relative to others. These findings are broadly consistent with the literature.

Our most important finding is that nominal wages, the canonical measure of agglomeration economies, seldom capture the costs of working and living in cities. These costs include higher housing costs, time lost in commuting as well as dis-amenities such as pollution or crime. Our metaanalysis shows that studies controlling for urban costs find elasticities to be 4.2 percentage points lower than studies that do not, implying a net agglomeration elasticity of 0.1 percent for developed countries, when using labor productivity as an outcome measure. Although our analysis confirms the relatively higher “gross” wage elasticities with respect to density; we find no evidence for “net” gains in light of high and increasing costs of working in developing country cities.

Further, rather than developing country agglomeration estimates being much higher than advanced countries as noted in country studies using wage data from China and India (e.g. Chauvin et al., 2017), there is no statistically significant difference between developing country and developed country estimates
**Figure 1:  China and India Shares of World GDP, Pre-Industrial Revolution (ratio)**

Source: Author‘s presentation based on data from Maddison.

Growth was also largely determined by these large population economies as well. During the first millennium, their growth lagged the rest of the world; however, in the following centuries, the two countries contributed to roughly half of world GDP growth. The composition of that contribution changed as China and India alternated in terms of stronger or weaker growth periods leading up to the industrial revolution (Figure 2).

**Figure 2:  Contribution to global growth of China and India, Pre-Industrial Revolution (%)**

<!-- Start of picture text --> 1 to 1000 1000 to 1500 1500 to 1600 1600 to 1700 1700 to 1820<br><!-- End of picture text --> Source: Author‘s calculations based on data from Maddison.

It should be noted that the calculation of the contribution to growth over these centuries is somewhat misleading, given that annual growth rates were minimal, as displayed in Table 1.

4
(corresponding to YA in Figure 1), **an** assumption that is clearly at<sup>odds</sup> with Levine's Table 2 (derived frots Borus) showing differing training costs for these three training modes. Thus little credence can<sup>be given to the</sup> particular rates of return results presented in Levine's paper,<sup>a conclusion</sup> that is buttressed by the findings, presented earlier in the<sup>present paper,</sup> that earnings do not differ significantly across the main<sup>training modes,</sup> over seven years of post-training experience in the labor market.

Summary and Implications The earnings of 1233 !ormer trainees in Israel were monitored<sup>over</sup> a seven **year** period. Earnings functions were estimated in<sup>the form of a</sup> series of v. ltiple regressions, with annual earnings as the<sup>dependent</sup> - variable and type of training program attended vocational secondary<sup>school,</sup> traditional apprenticeship, factory-based industrial school<sup>and short</sup> - Ministry of Labor teenage course included amongst the independent variables. Generally, no significant differences in the earnings<sup>of the</sup> graduates of the different modes were found, in a series of<sup>regressions run</sup> on annual earnings data for the years 1969-1975.

These findings viewed against the relative costs of alternative training modes confirm those of an earlier study by Michael Borus relating to a much shorter post-training earnings follow-up period; they suggest that,<sup>on</sup> cost-effective grounds, the balance of training provision<sup>for youth in Israel</sup> is not e*,ficient. The vast majority of skilled workers are trained in relatively expensive vocational secondary schools which, perhaps surprisingly, offer no
Table 2: Number of exporting firms and destination markets

|Destination|**2007**|**2008**|**2009**|**2010**|**2011**|**2012**|**2013**|**2014**|**2015**|**2016**|**2017**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Number of exporting firms to LAC|5,615|5,815|5,696|5,098|5,255|5,520|5,508|5,450|5,604|5,612|5,738|
|Number of exporting firms to LAC only|3,383 3|,713|3,669|3,114|3,286|3,526|3,535|3,462|3,518|3,523|3,621|
|Share of LAC firms in total firms|0.68|0.69|0.70|0.69|0.71|0.73|0.71|0.70|0.69|0.68|0.68|
|Share of LAC onlyfirms in total firms|0.41|0.44|0.45|0.42|0.44|0.46|0.46|0.45|0.43|0.43|0.43|

Source: Author’s calculation based on Colombian customs data.

Note: This table displays Colombian firm-level export dynamics to Latin America and the Caribbean (LAC), measured in absolute (number of firms) and relative terms (share in
As diaries were collected by survey teams during their second visit, „completion‟ is defined as a household having continuously filled in the diary up to this point.<sup>4</sup> It must be noted that the amount of effort expended by UBOS on implementation of the diaries was very limited; i.e. there was neither a standardized training nor any written training material that would explain the exercise and the nature of the input expected from them to local monitors.

# **3. Assessing the suitability of using diaries**

A key concern raised in diaries surveys in the literature has been that their application may be biased in favor of the well-educated and that, after an initial period of enthusiasm, respondents‟ interest may well drop off, jeopardizing data quality. Our data allow us to empirically explore to what extent these concerns did arise in practice. We find that (i) the incidence of drop-outs is limited; (ii) non-response is more likely for the well-educated rather than the illiterate; and (iii) although the number of entries per crop declines slightly over the course of the survey, the number of crops remained virtually constant.

> 2 Respondents are reminded to fill in the booklet for any crop harvested as soon as possible after harvest.

> 3 In practice, conversion of local units proved to be a major issue as the size and kilogram-equivalent of local units varies by product and location. To deal with this and allow conversion of non-standard units such as heaps, bunches, buckets, baskets and tins, UBoS decided to subsequently administer a market survey that required enumerators to physically weigh all relevant units. Drawing on this information allowed us to include all the information recorded in non-standard units, thus make use of virtually all the observations in the 2005 UNHS.

> 4 The diary was expected to be collected during the survey teams‟ second visit which occurred on average some 5 months after the first visit.

6
The first round of phone surveys was conducted in June and July 2020, the second round in August and September 2020, and the third round in October and November 2020. While most survey questions were asked round-by-round, recall of sales and profits was elicited at a more frequent monthly interval with respondents asked to recall values for each month since the previous survey round. Hence, for these business performance outcomes, we have recallbased monthly phone survey data from February to October 2020.

Response rates for the phone surveys were high with 83% of the sample reached in all three rounds and 91% in at least one round. Attrition is uncorrelated with treatment status.

# **3.3. Overlapping Timeline**

The timing of the follow-up phone surveys overlaps with the rollout of BDS components in our sample. By the first survey round in June, the classroom BDS sessions had been completed, counseling sessions had just begun, and digital BDS was not yet available. The latter was introduced in August, coinciding with the start of the second survey round. Both counseling and digital BDS continued to be rolled out through the third survey round in October, with the counseling sessions spanning June-December and the digital BDS repository open from August-November.

The pooled “Any BDS” indicator variable described in section 3.1. is based on eventual treatment assignment. While this identification strategy is independent of treatment rollout timing and is therefore the simplest to implement, it can depress the average treatment coefficient of “Any BDS”, since the full suite of BDS treatments only became available in the later survey rounds.

An alternative strategy is to allow the “Any BDS” indicator to vary by survey round depending on which treatments were in place at the time each survey was conducted.<sup>7</sup> Appendix Table 2 presents the round-by-round analysis following this strategy and the results are discussed in section 5 below.

Regardless of which strategy is used, it is important to note that the results on BDS should be viewed as
regulation (20). Panel C shows that almost 60 percent of endogenous changes (or 18 out of 31) are associated with bad times and the remaining cases with good times.

Figure 7 shows endogenous and exogenous changes in the ECRR measure for each country, as well as the composition of endogenous changes into those corresponding to measures aiming at offsetting output fluctuations in good and bad times. Macroprudential use of RR (i.e., endogenous changes) has been common in our three Latin American economies in the period surrounding the 2008 global crisis. Interestingly, yet not surprisingly, the use of RR for macroprudential (i.e., output stabilization) purposes has not been, by any means, a recent phenomenon as some of the latest papers in the literature seem to suggest. Changes in RR have been frequently used for countercyclical purposes in the past. For example, the central banks of Argentina and Brazil actively used them before and after the financial crisis of 1995. Argentina also reduced the RR on several occasions in 2001 in an attempt to stimulate economic activity after several quarters of negative output growth.

# **5 New measure of central bank interest rate shock**

The exogenous shock to the interest rate is calculated based on the strategy proposed by Romer and Romer (2004) and relying on data from the World Economic Outlook (WEO) historical forecast data. This dataset contains 2-years of historical data and 6-years of forecast data, for three variables: GDP growth, inflation, and the current account balance as percent of GDP. The 6-years of forecast data appear twice every year, once in the Spring and once in the Fall. For instance, in 1991 there is historical data for 1989 and 1990 as well as forecast data for the years 1991-1996 that were projected in the Spring and in the Fall.<sup>19</sup> The Spring forecast of inflation and GDP growth is used as the forecast for the second and third quarters while the Fall forecast is taken as the forecast
# **Figure 4: Modal pattern for commuting journeys in the Metropolitan Area**

# _Source:_ OPSM, November 2002

2.17 Finally, since the demand for urban transport services is a derived demand for other services such as education, health, shopping and leisure, it is harder to come-up with a meaningful concept of subsistence. Furthermore, since the 2002 survey was not able to collect information on journeys other than those related to head of household commuting, there is no real information base for deriving a subsistence concept. Therefore, the cost of one typical round trip commuting journey per day is used here as a very simple approximation to the subsistence concept. This amounts to US$0.67 per day or US$14.9 per month, which is almost 25% more than what the first quintile heads of household are currently spending, given their observed tendency to switch out of public transport.

# **SUMMARY**

2.18 In summary, this evaluation of social policy needs would appear to provide support for a universal access policy aimed at expanding coverage of water services in the Metropolitan Area sewerage services nationwide, and possibly also natural gas services. This could be achieved via subsidies aimed at reducing connection costs, and/or the cost of complementary investments within the household. This can be regarded as a long-term policy objective, whose justification is independent of the economic crisis that afflicted the country in 2002.

2.19 At the same time, infrastructure services that were reasonably affordable to all back in 1997, have recently become very expensive in relation to the income of households in the first quintile. This changing situation is attributable both to rising prices and falling real incomes. This implies the need to develop social policy mechanisms to maintain the cost of the subsistence basket within an affordable range for the poorest households, particularly given the prospect of upward tariff adjustments to compensate infrastructure service providers for the devaluation of the peso.

12
2,703,543.11|1,135,848.02|
|Manufacturing|37,365.53|63,454.85|102,114.36|121,943.68|
|Construction|28,736.80|41,179.33|29,381.44|52,645.89|
|Trade|21,434.30|50,142.16|52,920.75|67,759.58|
|Transport|50,617.23|84,467.84|115,409.41|141,432.79|
|Business|49,032.70|102,087.52|99,035.22|190,163.04|
|Other|29,823.28|40,417.39|55,222.15|60,091.45|
|_Aggregate_|_41,370.36_|_63,251.20_|_77,165.23_|_91,074.25_|
|_Aggregate excluding mining_|_31,146.60_|_53,345.30_|_67,307.20_|_84,613.40_|

Source: Authors’ calculations based on data from DOSM Figures 10 and 11 show that there are large labor productivity gaps between sectors in Malaysia. In 2018, the productivity gap between the most productive sector (business services) and the least productive sector 14