rafmacalaba/datause-encoder-data huggingface dataset:
7 Inst!tutions. The perceived failure of credit markets to urovide funding for worthy agricultural activitles can often be traced to Inadequate public Investment In legal and phy8lcal lrarastructure, enforcement mechanisms, and commodity risk mitlgating arrangemente which would make lending to agriculture a more profitable undertaking.

11. Fungibility of money The effectiveness of attempts to address 'he Inadequacy of market-Induced Institutional credit to agriculture through governme-At Intervention Is often hindered by the fungiblilty of money. In many Instances, unless costly supervislon Is undertaken, borrowers can use funds for purposes preferable to them, regardless of the cbJectlves promoted by policy makers. Furthermore, It Is Impossible to ensure that borrowed funds are used to finance more Investment than would have taken place otherwise, with funding from other sources. Additional loan funds may thus generate otGy a partial iri:rc ie In Investment, especlally If the profitabillIty of agriculture Is low and farmers have other, more attractive Investment or consumption opportunities. Two OED studies on the offect of agricultural credit found tlhat substitutlon of funds was a major factor responsible for the limited success of credit In enhancing productivity.<sup>8</sup> For example, of the funds provided through Bank-supcorted credit projects In Mexico, Pakistan, and the Phillppines, only 25-50 percent were estimated to have added to agricultural Investment. The common argument that subsidized credit should compensate farmers for other policlis which penalize agriculture (e.g., price controls, overvalued exchange rates and commodity export taxes) Is frequently not valid, because the subsidy does 8 OED, 'Kenya, Impact Evaluafon Report First SmalJholder Agriculural Credit ProJect", Report No. 2968, May 5, 1980; OED, *Agrkulural Credit _Progmams,_ Report No. 1357,1976 (A otudy of 24 **cowntries).**
3 to these items.<sup>4</sup> Industrial imports are broken down to groups identified in the Agreements in terms of the CM. For each CEE-5 country, the appropriate range of imports and of NTBs to be considered is denoted in the SMART data base. Two major indicators, extracted from SMART, are employed. The first is the proportion of imports subject to restraints, i.e., the NTB coverage ratio. The second is a simple arithmeic average of tariffs calculated over a group of tariff lines.

There are three problems with using these measures as indicators of market access before and after the entry into force of the liberalizing measures stipulated in the ITAs. The first, relating to indicators of market access, is general-not country- .or region-specific. The problem is that both NTB coverage ratios and tariff averages tend to be downward biased in terms of measuring restrictiveness, albeit for different reasons. The NTB coverage ratio downplays the restrictive impact because imports of products facing NTBs are depressed, lowering their share in total imports.<sup>5</sup> Average tariff rates are understated, especially on imports that are subject to GSP preferential rates within l[nits and above them to MFN rates. (SMART does not take account of these limits.) Second, the SMART data base has not been able to keep pace with the dramatic shift in trade paerns of the CEE-5 and the changes in their access to EC markets. Its trade data is for 1988 while its inventory of nontariff measures and tariff rates is for 1990. As a result, the data base incorporates the GSP status granted by the EC to Hungary and Poland in 1990, but not that extended to Bulgaria and the FCSK in 1991. The changes in export composition which have taken place affect more the NTB coverge ratio An the unweighted tariff rate average, as the latter is not sensitive to the size of imports but changes only when new products are added. Thus, the primary utility of these indices is that they point to areas where the reduction of tariffs or NTBs would have an impact on EC imports from the CEE-5.

Another reason for treating the results of this analysis with caution is that NTBs are often used in response to increased pressure from imports. Growing levels of CEE-5 exports have already led steel and chemical producers to urge the EC to implement trade restraint. The irony is that some provisions of the 4The list of NTBs, containing 25 measures covers the major instrments used-by the Community to protect its markets. SMART can be used to generate information on average tariff rates (for a range of imports from a selected countay) and the percentage of imports affected by (selected) NTBS. The data base and procedures are described in UNCTAD/World Bank (1989).

5 For a comprehensive discussion, see Yeats (1979).
<!-- Start of picture text --> Health Deprivation - by State in Health Deprivation - by State in Health Deprivation - by State in<br>North Central - MICS North East - MICS North West- MICS<br>80% 80% 80%<br>70% 70% 70%<br>60% 60% 60%<br>50% 50% 50%<br>40% 40% 40%<br>30% 30% 30%<br>20% 20% 20%<br>10% 10% 10%<br>0% 0% 0%<br>child 0-1 child 0-1 child 0-1<br>Benue FCT Abuja Kogi Kwara Adamawa Bauchi Borno Jigawa Kaduna Kano Katsina<br>Nasarawa Niger Plateau Gombe Taraba Yobe Kebbi Sokoto Zamfara<br>Health Deprivation - by State in<br>Health Deprivation - by State in Health Deprivation - by State in<br>South South MICS<br>South East - MICS South West- MICS<br>80% 80% 80%<br>70% 70% 70%<br>60% 60% 60%<br>50% 50% 50%<br>40% 40% 40%<br>30% 30% 30%<br>20% 20% 20%<br>10% 10% 10%<br>0% 0% 0%<br>child 0-1 child 0-1 child 0-1<br>Abia Anambra Ebonyi Enugu Imo Akwa IbomDelta BayelsaEdo Cross RiverRivers Ekiti Lagos Ogun Ondo Osun Oyo<br><!-- End of picture text --> Source: Authors’ estimates based on MICS 2016/17 Note: Individuals with missing age were dropped from the analysis. These Health Deprivation shares are based on the original definition by Gordon et al. considering those deprived that did not receive any immunization or no diarrhea treatment, when having diarrhea. As the age range is so small, the sample size does not allow a disaggregation by gender.

# Sanitation Deprivation

Severe sanitation deprivation has at the aggregate national level remained unchanged, but is especially a rural concern where about a third of the children are deprived, compared to the national average of around one quarter of the children. Unlike for other deprivations here little difference between deprivation rates for children living in the north versus south are observed. These estimates also closely coincide with the share of households overall practicing open defecation as reported in a joint UNICEF and WHO progress report on sanitation (UNICEF and WHO, 2019), but are around 10 percentage points higher than those based on the National Water Supply and Sanitation survey 2015 presented in WB (2017)<sup>24</sup> .

> 24  WB 2017 discusses data quality concerns of NWSS survey on page 17 Box 3.1

36
**Table 5. The ownership structure of the banking sector (% of total banking sector assets)**

||2002|2003|2004|2005|2006|2007|2008|2009|2010|
|---|---|---|---|---|---|---|---|---|---|
|**1. Domestic**<br>**investors**|**32.6**|**32.2 **|**32.5**|**30**|**30.3**|**29.1 **|**27.7 **|**31.9**|**33.8**|
|1.1. Banks with<br>major state<br>shareholding|25.1|24.4|20.6|20.3|19.8|18.3|17.3|20.8|21.5|
|1.2.<br>Commercial<br>banks with<br>major private<br>shareholding|2.5|2.6|6.6|3.9|4.3|4.6|5.0|5.3|6.2|
|1.3.<br>Cooperative<br>banks|5|5.2|5.3|5.8|6.2|6.2|5.4|5.8|6.1|
|**2. Foreign**<br>**investors**|**67.4**|**67.8**|**67.5**|**70**|**69.7**|**70.9**|**72.3**|**68.1**|**66.2**|
|2.1.<br>Commercial<br>banks|67.4|67.8|66.9|69.1|66.6|66.6|66.9|62.8|61.5|
|2.2. Branches<br>of credit<br>institutions|0.0|0.0|0.4|0.9|3.1|4.3|5.4|5.3|4.7|

Source: NBP, KNF.

**Table 6. Top 5 foreign investors in banking sector**

|Year<br>||Country (% of<br>|total Polish banking <br>|sector assets)<br>||
|---|---|---|---|---|---|
|2002|Germany (17.9)|Italy (14.1)|USA (8.6)|Netherlands<br>(6.8)|Belgium (5.9)|
|2003|Germany (18.2)|Italy (13.2)|USA (9.0)|Netherlands<br>(7.2)|Belgium (5.8)|
|2004|Germany (18.9)|Italy (11.2)|USA (8.7)|Netherlands<br>(7.9)|Belgium (5.0)|
|2005|Italy (21.1)|Germany (8.7)|Netherlands<br>(8.2)|USA (7.9)|Ireland (4.8)|
|2006|Italy (19.9)|Germany (8.4)|Netherlands<br>(8.2)|USA (7.8)|Belgium (4.9)|
|2007|Italy (17.4)|Netherlands<br>(10.9)|Germany (9.3)|USA (7.4)|Belgium (5.6)|
|2008|Italy (13.4)|Netherlands<br>(10.8)|Germany (10.2)|USA (8.6)|Belgium (6.1)|
|2009|Italy (13.3)|Germany (9.9)|Netherlands<br>(8.7)|USA (7.4)|Belgium (5.7)|
|2010|Italy (12.4)|Germany (10.4)|Netherlands<br>(8.6)|USA (6.9)|France (5.8)|

Source: NBP, KNF.

28
association with a survey question on “immigrants”.<sup>37</sup> Furthermore, while the responses correlate strongly with mutliple dimensions of attitudes toward immigrants, the literal interpretation of the question could yield a different interpretation of our results. Respondents answering whether it is a good area _for immigrants_ could explain, for example, column 1 of Table A1; places that have more rights for immigrants are likely better places for them to live, all else equal. However, this would not explain columns 3 and 5 of this table showing the same relationship using more precise measures on attitudes. Overall, we believe the measure, although imperfect, would be able to detect substantial shifts in attitudes based on the evidence presented in Section 4.1.

These results are preliminary and further work could amend these findings. We are exploring additional specifications that may provide better identification, for instance defining events across multiple years (instead of choosing the largest event) and evaluating spillovers explicitly at the country level and in neighboring regions to events. We are also working on a number of robustness checks, including to survey timing, weighting, aggregation, other outcomes, clustering of standard errors, outliers, and imputation methods, as well as more summary statistics to better describe the data.

# **6 Policy and Program Implications**

The mass arrival of refugees has been a major concern for a set of low- and middleincome countries. In this paper, we conduct an analysis of the impact of large-scale refugee arrivals on attitudes in these settings and discuss the role of policies on social cohesion and other outcomes for the host communities. Our preliminary findings are two fold: (i) on average across all regions with large, sudden flows, we find statistically insignificant effects on attitudes, but precise enough to rule out most

> 37At the country-level, refugees make up 32% of the immigrants in the countries in our main specification in 2010, when country-level data on immigrant populations is available (United Nations 2019). This share will be substantially higher in the specific years and regions we study.

34
- 74 -

**Table** 4.11: Costs of Electricity Generatlon by Type of Fuel

||Overall<br>Efficiency<br>percent|Capit<br>U.S.|al Costs<br>cents/kwh|Tot<br>U.S.|al Coats<br>cents/kwh|
|---|---|---|---|---|---|
|Coal<br>Nuclear|33<br>32|2.0<br>3.8|<br>-<br>4.3<br> <br>-<br>10.0|3.8<br>5.3|<br>-<br>6.9<br> <br>-<br>11.8|
|Fuel Oil|33|2.0|<br>-<br>2.5|4.8|<br>-<br>5.7|
|IGCC|29|3.3|<br>-<br>4.5|7.5|<br>-<br>8.9|
|Gas Turbine|32|0.8|<br>-<br>1.1|3.4|<br>-<br>13.9|
|Gas CC|45|1.4|<br>-<br>1.9|3.1|<br>-<br>3.8|

- (IGCC integrated coal gaeiflcation combined cycle Gas CC - natural gas combined cycle)

This range of figures illustrates that the assumption of equal capital costs reuiLred for the standard econometric approach is rather doubtful for certain technologies. The relative importance of running costs to capital costs is also quite variable so that the choice of fuel wlll depend not simply on the relative fuel prlce but also on the relative capital cost. To the extent that changes in capital costs have been greater for some technologies than others over time then the choice of fuels may have been affected as much by shifte in relative capital costs as by shifts in relative fuel prices.
this result, Urrutia and L6pez (1994, 1995) suggested that the acceleration of the financial liberalization process in the 1990s relaxed liquidity constraints causing an increase in consumption. In addition, Echeverry (1996) explained the drastic fall in the Colombian private saving rate taking a similar approach to that developed in the exchange rate based stabilization literature (i.e. Calvo and Vegh (1993, 1994)). He argued that nonliquidity constrained consumers increased their durable consumption due to their expectations regarding the effects of the trade reform on import prices and the temporariness of the high level attained by the real exchange rate. Finally, Steiner (1995) attributed to fiscal and monetary policies the fall in the private saving rate. On the fiscal front, the tax burden was increased to prevent a deterioration of the fiscal stance caused by the trade and political reforms (i.e. fiscal decentralization and the enhanced role of the government in the provision of justice and security)<sup>2</sup> . The monetary stance was modified in 1992 when the costs and limits of a two-year sterilization policy were evident. As a consequence, interest rates were drastically reduced, international reserves began to be intermediated by the financial system, credit increased, borrowing restrictions were relaxed and a so called consumption boom seemed to have occurred.

Despite the variety of explanations given to the recent decline in Colombian private savings, most analysts have not looked closely to the data and have failed to recognize that the apparently low level attained by private savings in the 1990s might reflect just data inadequacies. The paper is organized in the following way. Section 2 discusses some methodological issues and explains two important corrections that can be easily made to the saving measures presented in the Colombian National Accounts. In particular, it adjusts the saving measures by net capital gains from revaluations of assets and liabilities due to inflation and changes in the real exchange rate. As explained by Serven and Schmidt-Hebbel (1996), this exercise is useful because it constructs a saving measure consistent with net wealth changes and, therefore, with consumption theory. Section 3 makes the comparison between the adjusted and traditional measure of private savings. This shows that both of them have declined in recent years. However, whereas in 1992 the

> 2 The former had a negative impact on revenues due to the reduction of the import surcharge and the latter increased public consumption from 10% of GDP in 1990 to almost 15% of GDP in 1994.

2
Figure 1. Ratio of Biodiesel to Ethanol Prices <!-- Start of picture text --> 2.50<br>2.20<br>1.90<br>1.60<br>1.30<br>1.00<br>~ ~ORORRwWwWOwmOwWAWAWDHADADA AAA aoaaoeaogoocd’igerusHFAAwBRA AT NNN NNN<br>es99esee2999- 9S 9989S SR Re tte eee te ta<br>e<sZz20pgQ © wo JFP FO Pes@ Q+ © Z0sAHOR9 YOY B&BLesQa+ £C ZoAG@HLFszsZ0fWHo YF QB Qs&s £C wo ovKH YY LetsBOB Q+ £C Zo0KHLEZZ208HHoO FB foms+ fC wD HKoO YV<br><!-- End of picture text -->
# The State of Land Use in Northern Nigeria: A Landsat-Based Mapping Framework

Fernando Sedano,<sup>*</sup> Vasco Molini,<sup>†</sup> and M Abul Kalam Azad<sup>‡</sup>

**Keywords:** land degradation, Landsat, medium resolution, land-cover/land-use change, agriculture, multitemporal, Sudan-Sahel region.

## **JEL Classification:** Q150, Q160

> * Department of Geographical Sciences, University of Maryland–College Park; fsedano@umd.edu

> † Poverty and Equity Global Practice, World Bank; vmolini@worldbank.com

> ‡ Poverty and Equity Global Practice, World Bank; mazad@worldbank.com
2 in offsetting these shocks and covering the shortfall in food consumption. Finally, I test several hypotheses that postulate the factors that deteLmine the tendency of donors to respond to the needs of different countries. The study uses data for 1979-87, a period with fairly reliable figures on emergency food aid flows and agricultural production.

The results suggest that food aid and commercial food imports stabilize food consumption and neutralize the effects of random shocks to domestic production. Food aid compensates for up to 50 percent of the drop in food production; imports make up an additional 30 percent. In other words, every oneton drop in cereal production is offset by the delivery of 0.8 tons of cereal and dairy products from abroad. There is, however, a lag in this response over a four-year period, although most of the aid is received in one to two years.

The results with regard to the accusation that emergency food aid is discriminatory are quite surprising. The international response to food crises in Sub-Saharan Africa is not contingent on the form of government or the level of political and human rights violations. On the contrary, countries classified as socialist with military governments, and that have a low score in terms of protecting political, economic, and civil liberties, tend to receive more aid in emergencies.

The paper is organized as follows: The first section documents the stylized facts of food insecurity in Africa and shows the relative importance of emergency and total food aid to food production and food shortages. Section 2 suggests an empirical framework for the estimation and analysis of the correlation between food aid and food production; the results are presented in Section 3. The final section elaborates on the economic and political
# **Table A5: Change of material well‐being of respondents: average score, share of those reported improvement and deterioration of the well‐being**

|||averag|e score|||impr|oved|||wors|ened||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||2014|2015|2016|2017|2014|2015|2016|2017|2014|2015|2016|2017|
|Average|3.07|3.26|3.33|3.29|16.4|11.6|9.3|11.6|21.6|34.0|36.8|36.0|
||||Poor|and vuln|erable po|pulation|||||||
|Vulnerable|3.05|3.23|3.30|3.23|18.6|13.4|10.7|14.5|21.3|31.9|36.5|33.5|
|Official poverty|3.14|3.29|3.29|3.28|14.4|12.0|13.2|13.0|24.7|34.5|33.0|33.7|
|Moderatepoverty|3.14|3.29|3.30|3.29|12.6|9.7|10.3|11.7|24.2|34.1|35.1|35.3|
|||||Place o|f residen|ce|||||||
|Minsk|3.10|3.29|3.33|3.34|14.2|13.7|10.4|12.1|22.1|37.7|38.6|39.4|
|Large cities|3.07|3.32|3.37|3.31|17.9|10.0|9.7|12.6|22.6|37.5|39.3|37.5|
|Small cities|3.06|3.26|3.40|3.34|17.1|11.2|8.8|9.6|23.4|33.8|43.9|39.1|
|Rural area|3.04|3.17|3.22|3.20|15.6|12.6|8.4|11.1|18.5|26.1|27.2|29.2|
||||||Age||||||||
|Child|3.05|3.27|3.31|3.25|18.3|13.1|11.7|14.9|21.9|35.7|36.9|35.6|
|Working age|3.05|3.27|3.34|3.25|17.6|12.5|10.0|14.1|21.3|35.1|37.6|34.8|
|<br>Retiree|3.11|3.24|3.33|3.38|12.6|8.8|6.4|5.2|22.1|30.6|35.4|38.3|
|||<br>Empl|<br>oyment|<br>status fo|<br>r workin|<br>g age po|<br>pulation||||||
|Employed|3.02|3.24|3.31|3.24|18.3|13.0|10.1|13.6|20.2|33.6|36.6|33.9|
|Partly employed|3.07|3.32|3.38|3.27|19.4|14.4|11.8|17.9|24.2|38.9|40.1|38.9|
|Nonemployed|3.12|3.32|3.34|3.29|14.8|11.3|10.8|12.8|23.7|36.6|37.0|36.2|
|||Edu|cation l|evel for|working a|ge popu|lation||||||
|High education|3.05|3.28|3.31|3.24|18.9|13.1|11.8|14.8|22.6|36.2|36.7|34.9|
|Secondary specialized|3.05|3.25|3.34|3.29|16.8|13.0|8.9|13.2|21.0|33.4|37.5|37.4|
|Other|3.05|3.27|3.35|3.23|17.4|11.5|9.6|14.3|20.9|34.5|38.3|32.5|
||||Ty|pe of h|ousehold|(HH)|||||||
|HH without children|3.09|3.27|3.34|3.32|15.2|10.1|7.4|8.8|22.2|33.4|36.6|36.1|
|Retiree HH|3.11|3.24|3.33|3.41|12.0|8.1|4.9|3.1|21.1|29.9|34.0|38.3|
|HH with children|3.05|3.25|3.31|3.26|17.6|13.1|11.3|14.4|21.1|34.6|37.1|35.8|
|1 child|3.05|3.25|3.35|3.27|16.9|13.0|10.4|13.5|20.2|33.9|39.3|36.2|
|2 children|3.05|3.28|3.25|3.24|17.2|12.2|12.7|16.0|21.9|36.3|33.7|35.8|
|3 and more children|3.03|3.17|3.28|3.20|23.1|17.5|12.5|15.1|23.1|32.8|33.5|32.9|
|singleparent|3.11|3.37|3.36|3.43|14.9|11.6|13.0|9.2|24.1|41.6|39.8|42.3|

Source: Authors’ estimates based on HSS data.

32
# **What types of firms perform better than others?**

In this section we account for the variation in productivity (TFP) across firms that can be attributed to various characteristics of firms. The key characteristics of interest are ownership and export orientation; it is particularly important in the Serbian context to establish that, based on international experience, private ownership enhances productivity. The previous section also established that the productivity of firms is highly correlated with the country in which they operate. The analysis here augments the estimation equation used in column 2 in Table 1 with measures of ownership, export orientation, and also location (whether or not the firm is operating in a capital city). In the regression results, the estimated impacts on TFP of these firm characteristics are impacts that raise or lower the TFP of a firm compared to other firms in the same country.

**_International evidence._** The estimation used a sample of firms from 51 PICS-BEEPS surveys of firms in 44 countries. The estimations were done separately for manufacturing and services firms (Table 2). The omitted or benchmark category is state-owned, domestic, non-exporters and not in a capital city.<sup>12</sup> The results show that privately-owned firms, whether privatized or new private, have levels of TFP that are 30-38 percent higher than state-owned firms in the same country. Foreign ownership adds another 23-43 percent to TFP levels. Export orientation adds 22 percent to TFP (for manufacturing firms only).<sup>13</sup>

**Table 2: TFP regressions using firm-level data**

||**Manufacturing**|**Services**|
|---|---|---|
|Fixed capital|0.374**|0.268**|
|Labor|0.686**|0.698**|
|Privatized|0.382**|0.295**|
|New private|0.382**|0.289**|
|Foreign-owned|0.433**|0.226**|
|Exporter|0.216**|0.089|
|Capital city|0.092|0.178**|
|Country-survey dummy variables included|Yes|Yes|
|Number of observations|11,364 firms from 51 country<br>surveys|3,314 firms from 35 country<br>surveys|

** significant at the 1% level; heteroskedastic- and cluster-robust standard errors

This analysis can be extended to other measures of firm performance. Appendix 2 to the Investment Climate Assessment<sup>14</sup> reports the results using whether or not the firm reinvested any profits, invested in new plant in the preceding three years, and the log growth rate in its level of employment. The results reinforce those for TFP: in the international sample, private ownership and export orientation are good for firm performance.

**_Serbian evidence_** _._ What are the characteristics of productive, growing firms in Serbia, and how do these compare to those in the other PICS-BEEPS countries? We answer the first question by estimating the same regressions using only the sample of Serbian firms

7