rafmacalaba/datause-encoder-data huggingface dataset:
impact as a uniform transfer can be achieved at 23% of the cost (Table 3). These results confirm that not only are there gains from spatial targeting, but they can be of considerable magnitude.

# _Simulating the Impact of “Naïve” Geographic Targeting_

The optimization scheme implemented above is intuitively straightforward. But it is not always easy to describe and explain in non-technical terms exactly how much each commune should receive under this scheme. Given that the design and implementation of targeting schemes is often part of a political process, and that there is generally a need to be able to explain allocations in a simple and clear manner, it is of some interest to ask whether gains from spatially disaggregated geographic targeting are also significant when the poverty map is combined with simplistic, non-optimal, transfer schemes.

To simulate the impact of the “naïve” transfer scheme we start by taking our poverty map as the basic statement on the distribution of poverty in Morocco. On the basis of the poverty map we identify the localities that will receive priority in the targeting scheme (we consider initially regions, then provinces, then communes, then districts etc.). We calculate the amount _a_ that will be targeted to all persons in the priority regions (budget _S_ divided by the total number of poor people in the country, Np). We simulate the targeting scheme in turn for each replication _r_ by allocating _a_ to all persons in our priority regions (irrespective of whether, in replication _r_ , those regions are particularly poor or not) until the budget is exhausted. We re-calculate the post-transfer national poverty rate in replication _r_ . The average post-transfer national poverty rate across all replications provides our estimate of how poverty will have changed as a result of the transfer scheme. This expected poverty rate can be compared to the 15
# **References:**

- Barth, J., G. Caprio, and R. Levine, 2006, _Rethinking Bank Regulation; Till Angels Govern_ , New York: Cambridge University Press.

- Berger, A. N., N. H. Miller, M. A. Petersen, R. Rajan, and J. Stein, 2005, “Does Function Follow Organizational Form? Evidence from the Lending Practices of Large and Small Banks,” _Journal of Financial Economics,_ vol. 76, pp. 237-269.

- Brealey, R., and E.C. Kaplanis, 1996, “The Determination of Foreign Banking Location,” _Journal of International Money and Finance,_ vol. 15, pp. 577-597.

- Buckley, P. J. and M. Casson, 1991, _The Future of the Multinational Enterprise,_ 2<sup>nd</sup> Edition, London: MacMillan.

- Casson, M., 1987, _The Firm and the Market_ , London: Allen and Unwin.

- Di Giovanni, J., 2005, “What Drives Capital Flows? The Case of Cross-border M&A Activity and Financial Deepening,” _Journal of International Economics_ , vol. 65, pp. 127-149.

- Easterly, W. and M. Sewadeh, 2001, “Global Development Network Growth Database,” Washington, DC, TheWorld Bank.

- Focarelli, D. and A. Pozzolo, 2000, “The Determinants of Cross-Border Bank Shareholdings: An Analysis with Bank-Level Data from OECD Countries,” Federal Reserve Bank of Chicago, _Proceedings_ (May), pp. 199-232.

- Galindo, A., A. Micco, and C. Serra, 2003, “Better the Devil That You Know: Evidence on Entry Costs Faced by Foreign Banks,” Inter American Development Bank Working Paper No. 477.

- Grosse, R. and L.G. Goldberg, 1991, “Foreign Bank Activity in the United States: An Analysis by Country of Origin,” _Journal of Banking and Finance,_ vol. 15, pp. 1092-1112.

- Kaufmann, D., A. Kraay, and M. Mastruzzi, 2005, “Governance Matters IV: Governance Indicators for 1996-2004,” Washington, DC, The World Bank.

- Petersen, M.A. and R. Rajan, 1994, “The Benefits of Lending Relationships: Evidence from Small Business Data,” _Journal of Finance_ , vol. 49, pp. 3-38.

- Rajan, R., 1998, “The Past and Future of Commercial Banking Viewed through an Incomplete Contract Lens,” _Journal of Money, Credit and Banking_ , vol. 30, pp. 524-551.

- Stein, E. and C. Daude, 2004, “Quality of Institutions and Foreign Direct Investment,” Mimeo: University of Maryland and Inter-American Development Bank.

- Van Horen, 2006, “Foreign Bank Entry in Developing Countries: Origin Matters,” Mimeo, The World Bank.

- Williams, B., 1998, “Factors Affecting the Performance of Foreign-Owned Banks in Australia: A Cross-Sectional Study,” _Journal of Banking and Finance,_ vol. 22, pp. 197-219.

- Yamori, N., 1998, “A Note on the Location Choice of Multinational Banks: the Case of Japanese Financial Institutions,” _Journal of Banking and Finance,_ vol. 22, pp. 109-120.

16
4 and Singapore (Luan, 2010). There is also some literature on how to determine the economically optimal level of water losses reduction (Wyatt, 2011). As for what drives NRW, the literature is rather scant – even in developed countries. This is an interesting finding, as one would assume that one would like to know more accurately what drives NRW to determine the best way forward in reducing water losses. This may reflect the rather engineering focus on reducing water losses. Overall, the existing studies provide different explanations as to what impacts NRW. Skipworth et al. (1999) show in a study in England, that a large number of mostly technical and environmental factors affect municipal leakage rates. These factors include the age of the systems, the length and type of networks, pressure in the systems, climate, soil conditions, traffic loading, and density of connections. These authors also mention that topography can explain regional differences in water losses between utilities. Farley and Liemberger (2005) note the importance of physical factors, but these authors also put a lot of emphasis on management factors. Poor (management) practices, poor materials and infrastructure, local and political influences and social, cultural and financial factors are identified as factors driving the levels of NRW. They do not get into detail in how far these factors drive NRW and how this affects the design and implementation of water loss strategies. In a study by Gonzalez et al. (2011) on why NRW is so high in developing countries, the authors conclude that the lack of incentives is the main reason for differences in water losses between utilities. Water utilities normally have few incentives to undertake the necessary actions in order to reduce NRW, because they lack the income to pay for the cost associated with a reduction of water losses, while corruption and a lack of knowledge of users about the levels of NRW and the associated costs to users and taxpayers further add to the lack of interest to plug water leaks. In a follow-up study for Spain, using data from 133 municipalities, Gonzalez-Gomez et al. (2012) conclude that NRW measured as percentage of system input volumes is driven by not only physical and management indicators but also the environment in which the utility is located. In their study, the management quality of the utility is captured by indicators like tariff structure, indebtedness of the utility and different forms of management (private sector management and outsourcing of management). In their model, environmental factors are captured by population growth, the percentage of population outside the main village, and population density. The physical indicators are referring to the minimum water percentage of the storage reservoir and the type of distribution system (distribution systems by gravity or pumped) – with this last variable being a very important driver of NRW in these 133
Zenklusen, O. (2007). Natural disasters and economic development: A neoclassical review of theoretical perspectives and empirical evidence. Dissertation, University of St. Gallen, Switzerland.

World Bank (2006). Where is the wealth of nations?, Washington DC, World Bank.

World Bank (2007). World Development Indicators (WDI), Washington DC, World Bank. World Bank (2008). World Development Indicators (WDI), Washington DC, World Bank.

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capital requirements. Baumol et al. (1981) defined entry costs as _“anything that requires an expenditure by a new entrant into an industry, but that imposes no equivalent cost upon an incumbent_ ”, stressing the importance of sunk costs. The presence of sunk costs was later on shown by Baldwin (1989), Baldwin et al. (1989) and Dixit (1989) to lead to hysteresis in market structure and trade flows,<sup>1</sup> something that is close to our earlier observation that entry barriers into commercial farming lead to hysteresis in poverty.

If the conceptual issues are clear, the search for empirical evidence on the presence of entry costs is still largely limited to high-tech sectors in industrial countries, where, according to Geroski (1995) “ _econometric estimates of the height of entry barriers suggest that they are high_ ”. In the trade and development literature, the focus has been on the existence of barriers to export. Using Colombian manufacturing census data, Roberts et al. (1997) and Sanghamitra et al. (2001) found that sunk costs related to lack of exporting experience affected the aggregate export response, leading to hysteresis in trade flows. Sivadasan (2003) tested how reducing entry barriers through measures like trade and FDI liberalization would affect manufacturing productivitiy in India. Porto (2005) attacked the problem from a slightly different angle, looking at how removing government-related barriers to export (transport costs, custom practices, bureaucracy, regulation and corruption) would affect poverty in developing countries. He found those barriers to be a large 24.5% of the value of goods shipped, their removal having a non-negligible effect on poverty.

The type of informal barriers considered by Porto is likely to be relevant for entry into agricultural markets. Remoteness, whether resulting from geography or infrastructure decay, is likely to be a substantial barrier to entry into commercial farming, as is the lack of credit or intermediaries (sometimes from ethnic groups that were marginalized by nationalistic policies). Individual characteristics such as education and farm size are also likely to matter. The interaction between those factors and the presence of entry costs has however been largely untouched. One of the few papers approaching our concerns, Barrett (1997), looked into the effect of food marketing liberalization on trader entry in Madagascar. He showed

> 1See also Martin (2002) and Owen et al. (2002) for trade-related issues.

2
- Nores, M., Belfield, C. R., Barnett, W. S., and Schweinhart, L. (2005). Updating the economic impacts of the High/Scope Perry preschool program. _Educational Evaluation and Policy Analysis_ , 27(3):245–261.

- Oster, E. and Thornton, R. (2012). Determinants of technology adoption: Peer effects in menstrual cup take-up. _Journal of the European Economic Association_ , 10(6):1263–1293.

- Ozler, B., Fernald, L. C., Kariger, P., McConnell, C., Neuman, M., and Fraga, E. (2018). Combining preschool teacher training with parenting education: A cluster-randomized controlled trial. _Journal of Development Economics_ , 133:448=467.

- Paxson, C. and Schady, N. (2007). Cognitive development among young children in Ecuador the roles of wealth, health, and parenting. _Journal of Human Resources_ , 42(1):49– 84.

- Paxson, C. and Schady, N. (2010). Does money matter? The effects of cash transfers on child development in rural Ecuador. _Economic Development and Cultural Change_ , 59(1):187–229.

- Pop-Eleches, C., Thirumurthy, H., Habyarimana, J., Zivin, J., Goldstein, M., de Walque, D., and et al. (2011). Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders. _AIDS_ , 25(6):825–834.

- Powell, C., Baker-Henningham, H., Walker, S., Gernay, J., and Grantham-McGregor, S. (2004). Feasibility of integrating early stimulation into primary care for undernourished Jamaican children: cluster randomised controlled trial. _British Medical Journal_ , 329(7457):89.

- Premand, P. and Barry, O. (2020). Cash transfers, behavioral change promotion, and early childhood development: Experimental evidence from a government program in a lowincome setting. Policy Research Working Paper No. 8670, Washington, D.C.: World Bank.

32
spending shocks.<sup>10</sup> The methodology has the advantage of overcoming the issue of fiscal foresight, whereby anticipated fiscal policy changes may be incorporated into current economic decisions (Forni and Gambetti 2010; Leeper et al. 2012, 2013). However, this approach relies on the availability and quality of public spending forecast data. Additional caveats relate to the nature of fiscal projections: first, they may not be fully orthogonal to past macroeconomic trends; and second, they rely on subjective, heterogeneous assumptions about future macroeconomic developments.

# **2.4. Estimates of public investment multipliers**

While the empirical work on total public spending multipliers across a broad range of countries is voluminous, the subset of the literature that distinguishes public investment multipliers is limited and primarily focuses on advanced economies. In general, there is an emerging consensus that public investment tends to have a positive growth impact in the medium term (Auerbach and Gorodnichenko 2013; Eden and Kraay 2014; Furceri and Li, 2017; Ilzetzki et al. 2013; Izquierdo et al. 2019; Leduc and Wilson 2012). However, there remains considerable variation in the estimates of the output elasticity to public investment; in a meta-analysis of 68 studies, Bom and Ligthart (2014b), report that the range is -1.7 to 2.0. In reviews of the literature, Gechert and Rannenberg (2018) and Vagliasindi and Gorgulu (2021) also report that public investment multiplier estimates range widely with an average of about 1.5. Appendix table B1 provides a comprehensive review of public investment multipliers in the literature over the past two decades.

Empirical work focusing on EMDEs has been especially scarce, given data constraints and methodological challenges in identifying spending shocks. Nevertheless, limited research on EMDEs also documents important growth impacts of public investment. For instance, Miyamoto et al. (2020) report an increase in output by 0.4 percent over 4 years for a sample of 39 EMDEs. Ilzetzki et al. 2013) estimate a public investment multiplier of 0.6 on impact, increasing to 1.6 in the longer run, for a panel of 24 developing countries. Furceri and Li (2017) report smaller magnitudes for a sample of 79 EMDEs: a 10-percent increase in public investment induces growth of 0.4 percent over four years. Smaller effects are reported in Warner (2014) using a sample of 124 EMDEs: a change in public investment equivalent to 1 percent of GDP is found to spur only meagre (0.1 percent) output growth in the short run with no significant effect in the long run. The observed wide range of estimates of government spending multipliers has prompted additional inquiry into the factors that may explain these differences—discussed in the following section.

> 10 This approach was utilized recently in Abiad et al. (2016), Furceri and Li (2017), Honda et al. (2020), and Miyamoto et al. (2020) to estimate unconditional and state-dependent public spending multipliers.

7
treatment effect than students projected to attend more often. In this sample, the differences between students with high and low baseline projected attendance are statistically significant for the basic and savings treatments (p-value of 0.013).

Table 6 contains the estimated treatment effects for enrollment and school participation in 2006, the subsequent academic year. The first three panels contain estimates of students’ continued enrollment using administrative enrollment data provided by the Secretary of Education. Panel D and E contain self-reported enrollment and attendance data from our followup survey. To keep the outcome measures consistent, we only consider students who were in grades 6-10 in 2005 in Panels A through E. Panel F then contains self-reported enrollment and graduation data for students who were in the 11<sup>th</sup> grade in 2005 and should have matriculated to tertiary institutions in 2006. The columns are organized in the same format as in Table 5.

Panel A contains the estimated treatments effects, using our administrative enrollment measure, for all of the students who participated in the lottery (rather than just the 68 schools selected for surveying). The first row contains estimates for all of the students in the study. Overall, 70 percent of students in the lottery had paid their enrollment fees and enrolled in school in 2006.<sup>14</sup> However, the students who received the savings and tertiary treatments were significantly more likely to have re-enrolled in school than those who did not receive a treatment by 3.6 and 3.3 percent respectively. In contrast to the effects on attendance, only students receiving the basic treatment in grades 6-8 in Suba show a statistically significant effect while those in San Cristobal show no effect. And in San Cristobal where the comparison between the basic and savings treatments is the cleanest, the difference between the treatments is statistically significant at the 5 percent level (p-value 0.024). Thus, shifting the timing of payments does seem to significantly increase the fraction of students that re-enroll in school over the basic conditional cash transfer design.

The distribution of the result by sub-sample is similar to those of the verified attendance results, except that the difference between students projected to be likely or unlikely to reenroll is starker. Rows 2 and 3 show the effects by grade levels, and the effects are evenly distributed. The last two rows then divide the sample based on our estimated probability of re-enrollment.

> 14 This is likely an under-estimate of the number of students who continue to be enrolled both because of matching errors and because the data provided by the SED for some schools (mostly private) were reportedly incomplete. However, given our within school variation in treatment assignment, none of the research groups should be disproportionately affected by these issues.

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sector (or, more generically, on the largest of plants relative to the smallest of plants). For the organized sector, the aggregate impact is fairly neutral with respect to urbanization. The build out appears most significant in urban areas closest to nodal cities, while rural areas farther away are developed. By contrast, the aggregate impact for the unorganized sector was significantly less. This asymmetry for inter-district infrastructure differs from that of within-district infrastructure identified by Ghani et al (2012b), which linked to spatial movements in both sectors. This differential is reasonable, given the greater optimization in location choice that a larger plant will conduct and the ability of these plants to trade inputs and outputs at a distance. Nonetheless, we remain cautious about broad claims regarding unorganized activity beyond the manufacturing sector until further research can validate GQ’s limited roles in other ways (e.g., considering household-based surveys that extend outside manufacturing).

Our project contributes to a literature on the economic impacts of transportation networks and infrastructure investments in developing economies, which is unfortunately quite small relative to its policy importance. Beyond Ghani et al. (2012a), the closest related study is Datta (2011), who evaluates the impact of GQ upgrades using inventory management questions contained in the World Bank’s Enterprise Surveys for India in the years 2002 and 2005. Even with the short time window of three years, Datta (2011) finds that firms outside of nodal districts along the GQ network decrease their average input inventory (measured in terms of the number of days of production for which the inventory held was sufficient) relative to those located on other highways. He also finds that firms in districts closer to the GQ network were more likely to switch their primary input suppliers vis-à-vis firms farther away. These results suggest improved efficiency and sourcing for establishments on the GQ network after its upgrade.

Beyond India, several recent studies find positive economic effects in non-nodal locations due to transportation infrastructure in China (e.g., Banerjee et al. 2012, Roberts et al. 2012, Baum-Snow et al. 2012). These studies complement the larger literature on the United States (e.g., Fernald 1998, Chandra and Thompson 2000, Michaels 2008, Duranton and Turner 2011, ‐ 2012, Baum Snow 2007, Lahr et al. 2005), those undertaken in historical settings (e.g., Donaldson 2010, Donaldson and Hornbeck 2012), and those focusing on other developing or ‐ emerging economies (e.g., Brown et al. 2008, Ulimwengu et al. 2009, Holl and Viladecans Marsal 2011, Hsu and Zhang 2011). A related literature considers non-transportation 4
Policy Research Working Paper 5992

# **Abstract**

Croatia began to implement case-based provider payment reforms in hospitals beginning in 2002, starting with broad-based categories according to therapeutic procedures. In 2009, formal diagnostic related groups were introduced, known locally as _dijagnostičko terapijske skupine._ This study examines the efficiency and quality impacts of these provider payment reforms globally on the Croatian health system by analyzing data on five procedures in acute health care for 10 years, between January 2000 and December 2009. The five procedures are cataracts, pneumonia, coronary bypass, appendectomy, and hip replacement. Using data from the Croatian Institute for Health Insurance, this study finds that both broad-based and detailed case-based payment systems have improved efficiency as measured by a reduction in average length of stay, with little impact on the number of cases. These provider payment reforms have had no adverse impact on quality as measured by readmissions. While it is still too early to quantify the impact of Croatia’s introduction of formal diagnostic related groups, it appears that the introduction of both broad and detailed case-based payment systems has improved efficiency in acute hospital care.

This paper is a product of the Human Development Sector Unit, Europe and Central Asia Region.. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at eyeh@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team