rafmacalaba/datause-encoder-data huggingface dataset:
Figure 13. Protectionism in goods trade versus services trade <!-- Start of picture text --> 80<br>70<br>IND<br>ZWE IRN<br>60 QAT<br>KWT<br>BHR<br>PHL<br>50 IDN THA EGY<br>OMN<br>MYS LBN PAN TUN BGD<br>SAU VNM JOR NPL<br>40<br>BWA LKA DZA<br>CHN NAM<br>BLR ZAF MWI UGA VEN<br>30 UKR ITA CRI MEX YEM TZA URYPAK MLI KEN<br>FINFRA RUS TUR KHM NGA CIV LSO CMR RWA<br>BEL JPN CAN CHL KOR UZB BRA<br>20 MUS PRTUSA GRCAUT AUSDEUBGRCZE ALBESPDNKHUNGTMCOLKAZHNDKGZMOZMDGPRY ZMB GHA MARBDI ARGSEN<br>10 PER SWE GBRIRL MNG NIC DOM BOLTTO<br>GEO ROU<br>NZL LTU ARM ECU<br>POL NLD<br>0<br>0 2 4 6 8 10 12 14 16 18 20<br>Average applied Most Favored Nation (MFN) tariff (percent)<br>Services Trade Restrictions Index (STRI)<br><!-- End of picture text --> Sources: UNCTAD TRAINS (via WITS), World Bank Services Trade Restrictiveness database (Borchert et al. 2012) and authors’ calculations.

Bank sector policies in Thailand, Philippines, Malaysia, and Vietnam restrict greenfield entry and operations. In Thailand, the limit on foreign ownership in a “local bank” was 49 percent, and there was a limit on operations: the number of branches and ATMs allowed per subsidiary was 20. In the Philippines, greenfield entry was not possible since the license limit of 10 had been reached, and for acquisition, the foreign ownership limit was 60 percent. In Malaysia, with the enactment of the Financial Services Act 2013 and the Islamic Financial Services Act 2013 in June 2013, there was a comprehensive modernization and streamlining of Malaysia’s regime on licensing and foreign equity limits in the banking and insurance sector (conventional and Islamic). In both conventional and Islamic finance, application for a license is now based on the prudential and “best interest of Malaysia” criteria. Similarly, the acquisition of a significant foreign equity interest in Malaysian banks and insurance companies could be up to 100 percent, subject to meeting the aforementioned criteria. In the context of the TPP negotiations, Malaysia promised to phase‐in further liberalization in the financial sector. Vietnam allowed wholly foreign‐owned subsidiaries but imposed a limit on the acquisition of banks. To acquire existing banks, the foreign ownership limit was 30 percent for aggregate foreign investment and 20 percent for a single foreign credit institution.

Most developing East Asian countries limited foreign investment in fixed and mobile telecommunications services. The limit on foreign ownership was 49 percent in Indonesia and Malaysia, and 40 percent in the Philippines. But Malaysia is progressively removing foreign 27
Table 2: Rainfall Shocks and Agricultural Yields

||Log<br>Yield|(Rice<br>/acre)|Log(agricultural<br>wage)|% of Area<br>Irrigated|
|---|---|---|---|---|
||(1)|(2)|(4)|(5)|
|**Small Cities and Towns Sample**|||||
|Rainfall Deviation|0.387***|0.448***|0.567**|14.53|
||(7.316)|(8.801)|(2.459)|(0.731)|
|Observations|696|696|458|355|
|Number of Upazila|232|232|208|180|
|**Rural Sample**|||||
|Rainfall Deviation|0.449***|0.498***|0.821***|27.94|
||(8.472)|(9.845)|(2.792)|(1.154)|
|Observations|696|696|436|386|
|Number of Upazila|232|232|205|195|
|Year & Upazila Fixed Effects|Yes|Yes|Yes|Yes|
|Area Characteristics|No|Yes|Yes|Yes|

Note: Rainfall Deviation is defined as the difference between log(current rainfall) and log(30 year average rainfall). The regressions in even numbered columns include a number of controls (log of travel time to Capital and/or Port cities interacted with time trend, flood prone dummy interacted with time trend, proportion of household with electricity, log of 1991 population interacted with trend, log of total active labor force, and proportion of labor force with above secondary education, share of urban households. All regressions include year and upazila fixed effects. Standard errors are clustered at upazila level. Robust t-statistics in parentheses *** p<0.01, ** p<0.05, * p<0.1
evidence has been found for India and other developing economies ( **Who creates jobs? New evidence from India** ).

<mark>Figure 10 provides a plot on new business entry density, defined as the number of newly registered corporations per 1,000 working-age people (those ages 15 to 64) for some 100 countries. Ethiopia, Rwanda, and other latecomers to development are at the bottom of this curve. They are substantially behind peer countries in rates of new business entry density, creating 0.03 new registered businesses per 1,000 working age people, compared to a rate of 2.28 in Brazil and 2.17 in Malaysia. In other words, those countries create new businesses at a rate that is orders of magnitude more than in Africa. A key challenge for latecomers to development</mark> in Africa will be to promote new business creation and entrepreneurship.

**Figure 10: Africa needs more entrepreneurs to create more jobs**

<!-- Start of picture text --> Business Registration Density<br>(Entrepreneurship Rates) by country, 2010<br>9<br>7<br>5<br>3 Brazil Malaysia<br>Korea, Rep.<br>Uganda Zambia Kenya Thailand<br>1<br>Rwanda<br>-1 Ethiopia<br>6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11<br>log(2000 GDP per capita, in constant PPP $)<br># new firms per 1,000 working-age population<br><!-- End of picture text --> Source: World Bank Group Entrepreneurship Snapshots 2010. World Development Indicators, 2010. Note: Countries designated as offshore tax-shelters excluded.

15
# **1. Introduction**

Previous literature (Stewart 2002) identifies two dimensions of inequality: inequality among individuals or households (vertical inequality) and inequality among regional, ethnic, and other categorical groups (horizontal inequality). There is evidence that horizontal inequality poses a greater risk for violent conflict, as compared to vertical inequality (Østby 2013). Although the relationship between inequality and conflict is not clear or direct, there is reason to believe that reducing inequality may help ease conflict between groups and thereby lower the risk of violence (United Nations and World Bank 2018). Earlier research (Celiku 2018) studies how social groups coalesce—around identity, status, feelings of humiliation, and the perception they are being politically shortchanged, among others—and the conditions under which their grievances can be mobilized. This research also argues that that reducing inequality and exclusion— particularly of women and young people—is fundamental to forging sustainable peace.

The history of Iraq over the past decade is a stark example of increasing vertical and horizontal inequalities, preceding and following a period of violent conflict. Research explores ethnic inequality with the help of night lights emissions from time-varying satellite data from 1990 through 2013 (Bormann et al. 2021). It finds Iraq exhibiting typical attributes of a weak state during the 1990s. At the start of the decade, Sunni Arab regions emitted slightly fewer nightlights per capita than the excluded Shia and Kurdish areas. But over the years, ethnic power relations and vulnerability to oil marginalized the Sunnis. This was further exacerbated post-2003, when the ethno-sectarian power-sharing arrangement designed to ensure communal stability further sustained an elite pact in which political parties captured and compromised formal state institutions. This was often facilitated by the ruling coalition's direct appointments of senior civil servants and bureaucrats, leading to higher institutional corruption (Dodge and Mansour 2021).

Past research also finds that horizontal inequality may reinforce individual-level inequality and cause various negative outcomes, including limited public goods provision and armed conflict (Bormann et al. 2021). The Islamic State, also known as ISIS, emerged from the Iraqi offshoot of the global Al-Qaeda terrorist organization. ISIS rose to prominence in 2011, taking advantage of instability in both Iraq and the Syrian Arab Republic to carry out attacks and strengthen their positions. In June 2014, ISIS seized the Iraqi cities of Mosul and Tikrit and announced the formation of a caliphate stretching from Aleppo in 2
worked at least one hour in the reference week. Among the non-employed, those individuals looking for a job during the previous four weeks and able to start work within two weeks were classified as unemployed. The remaining individuals were classified as inactive. In terms of formality, we regarded employees who are registered with the social security agency for their current job as formal-employed, while those not registered in the system were considered to be informal-employed.

As to the demographic characteristics of the participants, the survey includes questions on age, gender, marital status, education, number of children, and residence. Besides these demographic variables, SILC includes a diverse set of household income–related variables that allow us to determine whether the household receives any kind of social benefits.

Given the aim of this paper, which is to profile the relationship between labor market outcomes and social assistance in Turkey, we utilized SILCs in both a static and dynamic framework. In the static approach, we used the SILC 2013 cross section to estimate the relationship between the current labor status of an individual and the variables of interest. For 14+ individuals, SILC 2013 contains 47,827 observations. We weighted the observations with corresponding coefficients to achieve full representation of the Turkish labor market.

In the case of the dynamic approach, we estimated the relationship between annual labor market transitions and the relevant variables by utilizing the panel component of the SILCs. Ideally, the relationship would be estimated by using the observations on the latest possible transition period, namely, 2011–12. In this setup, we would utilize the two-year balanced panel component of the 2012 survey and be able to use corrected sample weights to gather countrywide representation.

However, one particular characteristic of the nature of labor market transitions limits the operational implementation of this approach. In point of fact, individuals generally show a great deal of inertia in moving from their initial position over the short term. For instance, 90 percent of individuals initially employed or inactive continued in that same status one year later; only the remaining 10 percent moved in different directions from their initial status.<sup>8</sup> Thus, there is scarce mobility in the labor market, which makes it difficult to identify a statistically significant relationship with a limited sample size.

> 8 Alcan, Can, and Pektaş (2015) provide transition probabilities in more detail.

12
(figure 1). (While there were some differences among countries, the rank ordering was similar across countries, so only the sample averages are reported here.) As in almost every country where investment climate surveys have been conducted, managers also perceived both the cost and accessibility of finance as a problem. And while they perceived infrastructure, access to resources, and technology as important constraints, they considered them less so than the policy environment.

**Figure 1 Share of Firms Identifying Each Investment Climate Factor as a Major Constraint in Five Transition Economies**

<!-- Start of picture text --> Macroeconomic instability (inflation, exchange rate)<br>Regulatory policy uncertainty<br>Tax rates<br>Cost of financing (such as interest rates)<br>Tax administration<br>Access to financing (such as collateral)<br>Corruption<br>Customs and trade regulations<br>Anticompetitive or informal practices<br>Business licensing and operating permits<br>Crime, theft, and disorder<br>Legal system and conflict resolution<br>Labor regulations<br>Skills and education of available workers<br>Electricity<br>Access to land<br>Transport<br>Telecommunications<br>0 5 10 15 20 25 30 35 40 45 50<br>Percent<br><!-- End of picture text --> _Note:_ Figure shows sample averages across the Kyrgyz Republic, Moldova, Poland, Tajikistan, and Uzbekistan. _Source:_ World Bank, Business Environment and Enterprise Productivity Extension Survey, 2003. **[**

# **Measuring the Investment Climate**

Managers’ broad perceptions of the investment climate give some indication of the most constraining business problems. But to understand the effect of the investment climate on 8
the EU. From the estimated coefficients, and the indexes themselves, this implies a combined or composite productivity gain in market services in Italy of 66.3 percent. Of this, most follows from domestic regulation (38.0 percent), with the rest following from removing discriminatory barriers, that is, greater openness (20.5 percent). Although closed by West European standards, Italy is actually relatively close to the OECD norm in terms of openness (Austria, Japan, Slovenia, and the Czech Republic all rank more closed). It is an outlier in terms of domestic regulation, being near the upper range for overall domestic regulation issues.<sup>33</sup> The CGE experiment involves an application of the basic GTAP model, using GTAP8 data (benchmarked to 2007, the same year as our regulatory and MFP data). The basic aggregation scheme is summarized in Table 7.

Table 7: Database aggregation

|sectors|regions|
|---|---|
|primary sectors|Italy|
|processed foods, beverages|rest of European Union|
|textiles and clothing|rest of world|
|chemicals, petrochemicals||
|motor vehicles<br>other machinery||
|other manufacturing||
|utilities, construction||
|commercial services||
|public services||

In the basic GTAP family of models, changes to MFP can be modeled through efficiency coefficients (Hertel, Ianchovichina, and McDonald, 1997). In particular, national production is modeled as follows.

In equations (6), (7), and (8), the terms _X_ , _V A_ , and _IN_ refer to domestic goods/services, composite value added, and composite intermediate inputs, indexed for sector _i_ and production region _r_ . The elasticity of substitution at the upper-nest, the value added nest, and the primary input nests are represented by _σi, σi,V A_ , and _σi,IN_ . Primary factors are represented by Φ. _Qj,i,r_ represents the set of intermediate inputs from sector _j_ used by sector _i_ in region _r_ . Both value added and intermediate inputs are modeled as inputs to a final CES-based production function (6). The full set of production equations for the system is CES, 33From Table 5, we are estimating the impact of moving Italy from a log market access index of 0.510826 to 0.312551, and from a log price control index of 0.788457 to 0.339374.

31
experiments was generated following Kuhfeld (2010)<sup>4</sup> and achieve a 100% D-efficiency. The REDD+ survey design resulted in 84 unique choice profiles<sup>5</sup> (Kuhfeld 2010, Vermeulen et al. 2008). We created a block design where each of the surveys were separated into blocks of six choice profiles, giving fourteen unique REDD+ surveys with six questions each. Carlsson et al. (2010) test for learning and ordering effects in CE surveys and show that dropping the first choice question can decrease the error variance of estimates. Therefore, we add an additional choice question before the six choice questions and drop the first choice question when conducting the analyses to account for possible learning effects. In order to account for possible ordering effects we reversed the order of the questions in half the surveys and obtained 28 unique versions of the REDD+ survey.

# **_Model and Estimation_**

The standard multinomial logit model, which has been the workhorse for analyzing discrete choice models for many years assumes that the respondents are homogeneous with regard to their preferences (the βs are identical for all respondents). This is a strong and often invalid assumption. Therefore, following the recent literature, we use a mixed multinomial logit model (MMNL)<sup>6</sup> that incorporates heterogeneity of preferences (Hensher and Greene 2003, Carlsson et al. 2003, Dissanayake 2013 _mimeo_ ). Assuming a linear utility, the utility gained by person _q_ from alternative i in choice situation _t_ is given by

> 4 The experiment design was conducted using the SAS experiment design macro (Kuhfeld 2010).

> 5D-efficiency is the most common criterion for evaluating linear designs. D-efficiency minimizes the generalized variance of the parameter estimates given by D = det [V(X,β)1/k] where V(X, β) is the variance-covariance matrix and k is the number of parameters. Huber and Zwerina (1996) identify four criteria (orthogonality, level balance, minimum overlap, and utility balance) which are required for a D-efficient experiment design (see also e.g., Carlsson and Martinsson, 2003).

> 6This approach is also referred to as the mixed logit, hybrid logit, random parameter logit, and random coefficient logit model.

16
# **SAN IGNACIO DE VELASCO**

<!-- Start of picture text --> 400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>-300<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>SANTA CRUZ/EL TROMPILLO<br>400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>TARIJA<br>350<br>300<br>250<br>200<br>150<br>100<br>50<br>0<br>-50<br>-100<br>-150<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br><!-- End of picture text -->

# **SAN JOAQUIN**

<!-- Start of picture text --> 500<br>400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>-300<br>SUCRE<br>250<br>200<br>150<br>100<br>50<br>0<br>-50<br>-100<br>-150<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>TRINIDAD<br>500<br>400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>-300<br>M ar-48 Aug-53 Feb-59 Aug-64 Feb-70 Jul-75 Jan-81 Jul-86 Dec-91 Jun-97 Dec-02 Jun-08<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br>Average for 1960-1990 (milimeters)<br>Precipitation Anomalies compared to<br><!-- End of picture text --> 25
# **Table 3-continued**

|Independent|W|eather S|tation<br>||Satellite||
|---|---|---|---|---|---|---|
|Variables|Temp|Clima|te All|Temp|Climate|All|
|Soil erosion|...|...<br>|-1970.|...|...|-1130.|
||||(9.43)|||(4.71)|
|Salinity|...|...|322.|...|...|1140.|
||||(1.88)|||(5.39)|
|% Sand|...|...|-356.|...|...|-263.|
||||(5.82)|||(4.06)|
|%Wetland|...|...|-1170.|...|...|-667.|
||||(7.64)|||(3.60)|
|Water capacity|...|...|543.|...|...|533.|
||||(10.98)|||(9.85)|
|Adj R<sup>2</sup>|.507|.658|.761|.597|.677|.792|

_________________________________________________________________ There were 1942 observations in each regression, weighted by acres of cropland.

48
-12-

in the last row of Table 3, interest margin (interest income minus interest expenses) as percentage in average deposits declined substantially from historical levels. 6 What about the growth of the financial system? As Table 4 indicates, traditional measures of financial deepening show improvements in 1980-82: both the real money stock (M2) and the liquidity ratio (M2 expressed as a percentage of GNP) increased in 1981-82 after steep declines in 1978-80. Notice however, that the growth rate of real M2 was reduced by more than one half between 1981 and 1982, from 34% to 16%. The level of real deposits showed similar increases in 1981 and 982.

The counterpart to increase in deposits on the asset side of the banking system was a rapid increase in real indebtedness of the private sector, especially in 1981, despite i) narrowing bank margins and ii) high lending rates. Total assets of the banking system grew in real terms by 31% and 18% in 1981 and 1982 (Table 5), assets of private domestic banks grew by 35% and 17%. In 1981, the rate of increase in the stock of credits to the private sector was 81% in nominal terms and 45% in real terms. Given that in that year the interest rate on loans was very high, the increase in the stock of credit meant a heavy repayment burden in the following years. In fact, "in the second half of 1982, most of real credit expansion was absorbed by the need to refinance part of the high real interest rates charged to private enterprises."17 With an inflation rate of 25% in 1982, the increase in the le An official report prepared at the time claimed that the interest margin of credits was negative in 1981 and the first quarter of 1982 (Colasan 1984b, p.477). The standard practice of banks in Turkey was to capitalize interest payments when they were due and thus increase the principal amount outstanding. In the meantime, interest payments that were not collected were recorded as income. Therefore it is highly likely that income statements, on which figures in Table 3 are based, overstated interest income.

17 World Bank, 1983, pp. 11-12. The same observation is made in the aforementioned report: "...the banks' inability to collect interest payments
# **Disaster Risk, Climate Change, and Poverty: Assessing the Global Exposure of Poor People to Floods and Droughts**

Hessel C. Winsemius<sup>1</sup> , Brenden Jongman<sup>2, 3</sup> , Ted I.E. Veldkamp<sup>3</sup> , Stephane Hallegatte<sup>4</sup> , Mook Bangalore<sup>4</sup> , and Philip J. Ward<sup>3</sup> 1 Deltares, Delft 2 Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, DC 3 Institute for Environmental Studies, Vrije Universiteit, Amsterdam 4 Climate Change Group, World Bank Group, Washington, DC

## **Keywords**

Poverty, floods, droughts, global scale, exposure, climate change

## **JEL**

Q54, I32, Q50, I30