rafmacalaba/datause-encoder-data huggingface dataset:
# The Reallocation of District-Level Spending and Natural Disasters:

# Evidence from Indonesia<sup>_∗_</sup>

Emmanuel Skoufias (World Bank) Eric Strobl (University of Bern) Thomas Tveit (University of Bern)

**JEL Classification:** R5, C33, Q54, C63, R11, H12, H72

**Keywords:** Natural Disasters, Damage Index, Public Finances, Budget Redistribution

> _∗_ This paper was financed in part by the Disaster Risk Finance Impact Analytics project of the Disaster Risk Financing and Insurance Program of The World Bank Group
across the surveys. This research design enables us to accumulate multiple internally valid subnational results while probing the generalizability of findings across contexts and cases (Dunning, Grossman, Humphreys, Hyde, McIntosh & Nellis 2019, Zhukov, Davenport & Kostyuk 2019) to the extent possible.

We analyze each of the surveys separately to account for the different sampling procedures and to ensure that we are making valid comparisons within cases according to the intended sampling structure. Because each survey provides different opportunities to explore elements of our theory, we present the analysis of each survey separately. Within each case, our analysis proceeds in two steps. First, we analyze whether IDPs have significantly different levels of social and political engagement by comparing IDPs to similarly at risk but not displaced persons in our sample. Second, to better understand the conditions under which IDPs report social or political empowerment, we unpack heterogeneity within displaced communities within Iraq and the Philippines by probing whether variation in the experience of displacement is differentially associated with our measures of empowerment.

# **4.1 Ethics, Methods, and Surveying IDP Communities**

Systematically surveying displaced populations in conflict and post-conflict contexts prompts a number of practical and ethical challenges. We have adopted a participatory approach to the research cycle to ensure that the research is appropriately designed, adapted and relevant to the context, and provides timely, accurate and useful information for policy-makers. We typically adopt a sequential mixed-methods design starting with a qualitative phase designed to inform the development of a survey instrument. In parallel, several exercises are used to engage stakeholders into a participatory design of the instrument. The resulting instrument is validated and translated and then reviewed and debated with key stakeholders and finally pilot-tested and adapted as needed. The digital data collection platform we developed for this work, KoBoToolbox, was designed to reduce the gap between data collection and the provision of results. Results are then use to engage into a dialogue with key stakeholders, including the affected community, to provide further context Displacement further poses a number of methodological challenges for survey sampling, especially for random samples drawn primarily on geographic boundaries. To overcome these challenges, we work with reliable sources of information on displaced populations such as UNHCR and IOM, depending on the context, to develop the best possible sampling frame. We then created separate strata for displaced populations and non-displaced populations, so as not to select exclusively on displacement.

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- [17] Ilzetzki, E., E. G. Mendoza, and C. A. Vegh. 2013. “How Big (Small?) are Fiscal Multipliers?” Journal of Monetary Economics 60 (2): 239-254.

- [18] Inoue, T., D. Kaya, and H. Ohshige. 2015. “The Impact of China’s Slowdown on the Asia Pacific Region: An Application of the GVAR Model.”Policy Research Working Paper 7442, World Bank, Washington, DC.

- [19] Kose, M. A. 2002. “Explaining Business Cycles in Small Open Economies: How much do World Prices Matter?”’Journal of International Economics, 56(2): 299-327.

- [20] Kose, M. A., C. Otrok, and C. Whiteman. 2003. “International Business Cycles: World, Region, and Country Specific Factors.”American Economic Review 93 (4): 1216-1239.

- [21] Kose, M. A., and E. Prasad. 2010. “Emerging Markets: Resilience and Growth Amid Global Turmoil.”Washington: Brookings Institution Press.

- [22] Kose, M. A., E. Prasad, and M. Terrones. 2009. “Does Financial Globalization Promote Risk Sharing?”Journal of Development Economics 89: 258—270.

- [23] Litterman, R.B. 1986. “Forecasting with Bayesian Vector Autoregressions– Five Years of Experience.”Journal of Business & Economic Statistics, 4 (1): 25-38.

- [24] Lubik, T. and F. Schorfheide. 2007. “Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation.”Journal of Monetary Economics 54: 1069—1087.

- [25] Magnus, G. 2011. “Uprising: Will Emerging Markets Shape or Shake the World Economy?” Hoboken, New Jersey: John Wiley and Sons.

- [26] Neumeyer, A. and F. Perri. 2005. “Business Cycles in Emerging Economies: The Role of Interest Rates.”Journal of Monetary Economics 52(2): 345-380.

- [27] Obiora, K. 2009. “Decoupling from the East toward the West? Analyses of Spillovers to the Baltic countries.” IMF Working Paper 09/129. International Monetary Fund, Washington, DC.

- [28] Sharma, R. 2012. “Breakout Nations: In Pursuit of the Next Economic Miracles.”New York: Norton.

- [29] Stock, J., and M. Watson. 2005. “Understanding Changes in International Business Cycle Dynamics.”Journal of the European Economic Association 3 (5): 968-1006.

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# **COVID-19, Public Procurement Regimes, and Trade Policy**<sup>*****</sup>

Bernard Hoekman,<sup>†</sup> Anirudh Shingal,<sup>‡</sup> Varun Eknath<sup>§</sup> and Viktoriya Ereshchenko<sup>**</sup>

# **JEL classification** : F13, F15, H57, I18

**Keywords** : COVID-19; export controls; trade facilitation; trade policy; public procurement; trade agreements

* We are grateful to Matteo Fiorini, Valeria Perotti, Michele Ruta and Albert Nogues Comas and an anonymous referee for helpful comments on a previous draft. This paper draws on an EUI-Global Trade Alert-World Bank project to monitor trade policy measures implemented during the COVID-19 pandemic. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

† EUI, Florence and CEPR, London (bernard.hoekman@eui.eu).

- ICRIER, New Delhi; EUI, Florence and WTI, Bern (ashingal@icrier.res.in).

- § World Bank (veknath@worldbank.org).

- ** World Bank (vereshchenko@worldbank.org).
15 task was separated from the dictator game by four rounds – ten minutes – of tedious practice moving the sliders, further suppressing any latent consistency bias.

**Table 1:  Pro-social attitudes and pro-social effort**

|Dependent Variable|: Ability-adjusted|Effort for Charit|y|
|---|---|---|---|
||I|II|III|
|Amount Sent in Dictator Game|0.016**|0.015**|0.019***|
||(0.01)|(0.01)|(0.01)|
|Location (D)||-0.001|-0.002|
|(1 = STAN)||(0.01)|(0.01)|
|Gender (D)||0.006|0.005|
|(1 = Female)||(0.01)|(0.01)|
|Age (in years)||-0.004|-0.003|
|||(0.00)|(0.00)|
|Belief that Charity was Paid||0.002|0.003|
|(5 = Complete Confidence)||(0.00)|(0.00)|
|Treatment (D)|||0.001|
|(1 = Risky Private Sector)|||(0.01)|
|Treatment (D)|||-0.006|
|(1 = Low CharityMultiplier)|||(0.02)|
|Constant|0.947***|1.016***|0.996***|
||(0.01)|(0.07)|(0.07)|
|R-squared|0.003|0.005|0.006|
|P-Value|0.037|0.231|0.168|
|Observations|1480|1480|1720|

Note: * p<0.1, ** p<0.05, *** p<0.01. Dependent variable is ability-adjusted effort. OLS specification, standard errors in parentheses. The dictator game variable is divided by 1000 for presentational convenience. Results are robust to specifying the dependent variable as the difference between public and piece rate effort.

# **_Pro-sociality and public sector salaries_**

The second question we address is whether pro-social individuals are less likely to enter the public sector when public sector wages are high or whether, as in Dal Bó, Finan and Rossi (2013), wages have no effect on the intrinsic motivation of new entrants. 187 subjects at the University of Indonesia were asked to choose between a piece rate compensation which benefitted themselves (private sector) or a flat salary and effort benefitting charity (public sector). This laboratory choice is not foreign to the UI subject pool. While the UI subjects have not already chosen to enter the public sector, unlike those at STAN, many express an interest in public sector employment and would be competitive candidates if they applied (though the great majority, in fact, will go into the private sector).
versus labor content of exports. We also look to see whether exports have become more or less important for wages and jobs in South Africa, relative to total domestic production as well as total employment.

# **a. Labor Value Added**

The LACEX data show that the total labor value added contained in South Africa’s exports has been growing robustly and steadily since 2001 (Figure 1). Growth in all the wages paid to produce exports including those to produce domestic inputs of exports—considering the indirect linkages—was 7.9% annually, reaching $34.7 billion in 2011 (up from $16.3 billion in 2001).

The labor value added supported by the indirect linkages with export activities is relatively more important and grew slightly faster than the labor value added directly supported by exports themselves. Growth in the wages paid to produce exports _directly_ over the last decade was 7.7% annually in nominal terms, reaching $15.4 billion in 2011 (up from $7.4 billion in 2001). Growth in the wages paid to produce exports _indirectly_ was 8.1% annually, reaching $19.3 in 2011 (up from $8.9 billion in 2001).

**Figure 1: Direct and total labor content of exports, South Africa 2001-2011**

<!-- Start of picture text --> 2000 2005 2010<br>Year<br>Direct LVAX Total LVAX<br>40000<br>30000<br>US$ Mil<br>20000<br>10000<br><!-- End of picture text --> _Source:_ Authors’ elaboration based on LACEX.

However, labor value added per unit of exports in South Africa has declined since 2001 (Figure 2 and Table A1), witnessed in both the direct and indirect LVAX shares in spite of the nominal value of both direct and indirect LVAX increasing. In 2001, each $100 of gross exports generated $41 of domestic wages (of which $21 came directly from the export sector, with the remaining $19 coming through backward linkages to the domestic economy), while by 2011 this figure had reduced to $33 ($16 directly and $17 indirectly). The more pronounced decline in the direct than the indirect LVAX share is a result of the slightly higher growth and greater importance of the indirect labor value added in South Africa’s exports.

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competition - local prices are amongst the highest (Table 6) and per-capita-consumption amongst the lowest in East Asia (Table 7).

**Table 6. Cement prices are the highest ...**

**Table 7. ... and consumption is the lowest**

|**_Cement_**|**Price (US$ per tonne, Q4-06)**|**_Cement_**|**Per Capita Consumption (kgs)**|
|---|---|---|---|
|**Philippines**|**72**|China|-|
|Indonesia|69|India|-|
|Vietnam|65|Malaysia|477|
|India|52|Thailand|450|
|Thailand|50|Vietnam|316|
|Malaysia|49|Indonesia|144|
|China|35|**Philippines**|**128**|

_Source:_ World Bank, 2007 on JP Morgan and National Associations _Source:_ World Bank, 2007 on Cement Manufacturers Associations

# **2c. The rest of the private sector** **_does not need_ to invest**

**Economic growth is led by services.** In average, in the past few years, agriculture kept growing slower than GDP, at almost 5 percent, and industry continued to grow on pace with GDP, at nearly 5.5 percent.<sup>32</sup> In the same period, growth and profits came from the service sector. Boosted by private services (telecoms, electronics assembly, finance, voice-based BPO, and ICT-enabled services) and driven by a double-digit export growth (Figure 23), the sector is the economy’s fastest growing (although not able to provide adequate employment opportunities), expanding at 6.3 percent and accounting for 3 percentage points of total GDP growth in 2006 (Figure 15).

**The nature of growth is becoming less capital-intensive.** While in recent years the investment in manufacturing has been consistently declining, the investment in services was stable, and – despite its relatively low level – able to support the sector’s steady growth (Figure 16). As the service sector is less investment-intensive than industry, future economic growth is compatible with lower investment rates than implied by historical data. To enjoy rising profits, the service sector does not need to increase investment faster than GDP growth rates.

> 32 Mining - despite its untapped potential - witnessed a contraction.

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Dynamics. We supplement our cross sectional evidence by running a dynamic model of fertility. The unavailability of migration data for periods prior to 2000 prevents us to estimate a panel regression model. Nevertheless, it might be interesting to estimate a model linking the change in fertility rates with the distance between the prevailing fertility rate and the fertility rate at destination. Introducing inertia in a dynamic model makes the implications of our results stronger, for instance in terms of convergence. Since the fertility norm validated by our cross sectional analysis is log(n<sup>d</sup> ), we run the following regression: The key coe¢ cient is a1: Our model of transfer of norms implies a1 < 0 : countries with fertility rates higher (resp. lower) than their fertility at destination are expected to see a decrease (resp. increase) in their fertility rate. We use the change in fertility rates between 2000 and 2005 as the dependent variable. The model is estimated with OLS and involves di¤erent samples. Table 8 and 9 summarize the main ...ndings. Table 8 use the observed migration stocks to build <u>nt</u><sup>~~d~~</sup> : Columns 1 to 4 use OLS while columns 5 and 6 use IV to deal with the prossible endogeneity of ln (p0;t) : Table 9 provides exactly the same estimation results, but using predicted bilateral migration stocks instead of observed ones, as done in the previous section. This con...rms the existence of a �-convergence process. The average value of a1 across the four regressions is about -1/8. Focusing on the terms in nt and <u>nt</u><sup>~~d~~</sup> , equation (21) can be rewritten as: Equation (22) indicates that an equal proportionate increase in the 2000 fertility rate and the 2000 fertility norm raises the 2005 fertility rate by the same proportionate amount, with 7/8 of that increase due to the increase in the 2000 fertility rate and 1/8 due to the increase in the fertility norm. The migration rate has a positive impact on the 2000-to-2005 change in fertility rate in three of the four fertility change regressions (signi...cant at the 1% level in two of the four regressions and at the 10% level in a third one), which seems to make more sense than the negative and signi...cant coe¢ cients obtained in four of the sixteen level regressions.

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urban services. Poverty in the region has therefore been greater than an economic depression alone would have created.<sup>4</sup>

**Figure 1.1. Patterns of urbanization and growth in the transition economies and middle income countries, 1960-1990**

<!-- Start of picture text --> 70<br>1990<br>65<br>1990<br>A C<br>60<br>55<br>1960<br>B<br>50<br>1960<br>45<br>40<br>2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000<br>GDP per capita (1990 US$)<br>world except low income ECA<br>Urbanization (%)<br><!-- End of picture text --> Source: Commissars to Mayors, p. 7 Much of this poverty has appeared in urban areas of the region. In most analysis of poverty in most countries, poverty is found to be predominantly rural (with a higher incidence in rural areas even if the majority of the total poor are not rural), for a variety of economic, social and political reasons. Yet although urban economies in general offer individuals a wide range of opportunity though a deep and diverse labor market, and the relative density of urban settlement makes it possible for many services to be provided at lower cost and with greater quality than in the rural context, urban poverty remains a reality even in high income countries. Poverty in cities can result from in-migration of the poor from elsewhere; it can also result from cyclical or structural mismatching of workers with available jobs; and from institutional or governance failures, whereby access to assets such as housing and services does not respond to demand of some groups who become increasingly excluded and disadvantaged. In the ECA countries rural-to-urban migration is no longer significant, although urban-to-urban migration continues. Income poverty in cities is therefore more an issue of the economy’s response to transition and other shocks, and of growing inadequacies in services— all of which undermine residents’ sense of security and empowerment and raise their vulnerability. Much of the inadequate supply response reflects the partial (or rudimentary) progress of structural reforms in some of the countries, which cripples the urban economy’s ability to foster enterprise and ensure good matching of workers to jobs.

Apart from the overall high levels of urbanization, the distribution of urban population, economic activity and infrastructure were not balanced across the system of cities in the transition economies.<sup>5</sup> A common 4 Defining structural poverty as the difference between observed poverty rates and those implied by change in GDP alone, it has been estimated that a 1.3 percentage point increase in structural poverty is associated with every additional percentage point of over-industrialization. Based on data for 13 countries in ECA. Source _: Commissars, Box 5.1_ .

2
World Health Organization (WHO) and Bangladesh Government guidelines, respectively. There are no Bangladesh standards for salinity in drinking water; however, according to the WHO the “palatability of water with a total dissolved solids (TDS) level of less than about 600 mg/L is generally considered to be good” (WHO, 2011). According to the secondary drinking water guidelines by the US Environmental Protection Agency’s (EPA, 2018), the drinking water standard for TDS is 500 mg/L that is equivalent to ~750 μS/cm of electrical conductivity (EC) considering a ratio of 0.65 between TDS and EC (Rusydi, 2018). Finally, the maximum lifting capacity of hand-operated pumps in Bangladesh is 7-8 m below ground level (bgl) (UNICEF, 2010). We consider two threshold-based multi-hazard risk modeling of groundwater into four categories: extremely high, high, medium and low risks.

Groundwater risk map is based on the following criteria (Model 1) for four risk categories:

- Extremely High Risk: As > 100 μg/L & EC > 1500 μS/cm & GWD > 8 m bgl

- High Risk: As > 50 μg/L & EC > 750 μS/cm & GWD > 6 m bgl

- Medium Risk: As > 10 μg/L & EC > 750 μS/cm & GWD > 5 m bgl

- Low Risk: As > 10 μg/L & EC > 500 μS/cm & GWD > 4 m bgl

Groundwater risk map is based on the following criteria (Model 2) for four risk categories:

- Extremely High Risk: As > 100 μg/L & EC > 1500 μS/cm

- High Risk: As > 50 μg/L & EC > 750 μS/cm

- Medium Risk: As > 10 μg/L & EC > 750 μS/cm

- Low Risk: As > 10 μg/L & EC > 500 μS/cm

Groundwater risk maps are generated using the above sets of criteria in ‘R’ programming language (R Core Team, 2017). First, raster maps of spatial grid resolution of 2.5-km × 2.5-km for the three hydrological risk variables are generated using the Inverse Distance Weighting (IDW) algorithm in ESRI’s ArcGIS environment (software version 10.3.1). Raster data sets are imported into ‘R’ statistical software environment and the above sets of criteria are applied to individual grid points (total number of grids: 19,613 covering an area of ~148,000 km<sup>2</sup> ).

# **3. Results**

## **3.1 Groundwater risk mapping at the national scale**

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**_Energy demand models for policy_** **_<u>formulation</u>_**

# **Econometric approach**

The pioneering work of Houthakker (1951) on the British urban electricity consumption perhaps initiated the econometric investigation of residential energy demand in a formal way. Since then, and as with other applications, a wide variety of applications of the econometric approach to the residential sector has appeared in the literature. According to Bohi and Zimmerman (1984) and Madlener (1996), more studies have been done on this sector than any other area thereby providing an opportunity for detailed comparisons. Similarly, the focus on electricity demand is significantly higher than any other fuels.<sup>30</sup> However, in line with our preoccupation with forecasting models, we present a brief review here highlighting the major methodological developments. A more detailed recent review can be found in Madlener (1996), while Bohi and Zimmerman (1984) provide a somewhat older but excellent review of the US studies.

Residential energy demand studies have covered individual fuels (such as electricity, natural gas) or aggregate demand or the entire set of energies used. The reduced-form, single equation demand specifications are quire common for fuel-level analysis<sup>31</sup> . The log-linear specification is most commonly used in such studies for the ease of estimation and simplicity.<sup>32</sup> Although residential energy demand depends on the stock of energyusing appliances and other economic variables, in the short-run the demand is expected to be constrained by the existing capital stock, which in turn would influence the consumer response to any changes in the economic variables. To capture this aspect, some attempts were made to use two-stage demand analysis – one for the short-term and the other for the long-run. However, the data on appliance stocks is often poor and leads to problematic results.

The trans-log wave of the 1970s has also fed to the publication of a number of studies, including Pindyck (1979). In his study, Pindyck (1979) considered that consumers make

> 30 Some recent studies include the following: Ziramba (2008), Nasr et al (2000), Filippini and Pachauri (2004), Bose and Shukla (1999), Beenstock et al (1999) and Al-Faris (2002).

> 31 See for example, Taylor (1975) for a survey of electricity related studies.

> 32 Some recent studies of this type include Rapanos and Polemis (2006), Rijal et al (1990) and Blackmore et al (1994).

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