rafmacalaba/datause-encoder-data huggingface dataset:
# A. Balance Sheet Approach ‐ Joint Management of Assets and Liabilities

The joint management of assets and liabilities aims to facilitate the government’s evaluation of risk exposures holistically and to assess the feasibility of reducing net interest expenditure<sup>8</sup> and liquidity risk. Efficient implementation of ALM should be based on the availability of timely and accurate data on the assets and liabilities in the public sector, which usually are consolidated in a balance sheet. This section presents the responses of the survey participants on their practices with regards to the production, coverage, periodicity and publication of sovereign balance sheets.

## 1. Sovereign balance sheet

The preparation of a sovereign balance sheet allows policy makers to assess the government’s net asset or liability exposure in a comprehensive way and more easily identify mismatches. Producing a balance sheet facilitates discussion and cooperation among various actors and institutions across the public sector in order to compile data and determine what items should be included on the balance sheet (i.e. broad or narrow definition of SALM).<sup>9</sup> Once the format has been agreed and the data have been compiled, it becomes easier to quantify the net exposure and identify mismatches and natural hedges.

Almost all (90 percent) of the respondents indicated that their country does produce a balance sheet. The key findings are summarized below.

In terms of periodicity, the vast majority (84 percent) of the countries producing a sovereign balance sheet do so on an annual basis. Only two countries indicated that they update the sovereign balance sheet on a monthly basis, one country on a quarterly basis, and one country on an irregular basis (with the objective of producing it annually in the future).<sup>10</sup> Producing a complete financial statement based on the public accounts with exact numbers is a time‐consuming effort that requires significant institutional capacity (and a comprehensive accrual accounting framework), given the complexity of this task and the amount of resources it requires. Since the second option is more complex and requires more resources, the literature on SALM suggests developing, at least initially, a conceptual balance sheet, which identifies risks and vulnerabilities without necessarily quantifying them in detail. However, survey results

> 8 Or increasing net returns in the few cases when a sovereign earns net positive cash flows (country with a large SWF and low public debt for example).

> 9 In general, narrower definitions of SALM include the assets and liabilities of the government while broader definitions include contingent liabilities or even the present value of future revenue and expenditure.

> 10 A survey conducted by the IMF on analyzing and managing fiscal risks shows that 28 percent of the 80 countries surveyed are producing balance sheets. However, only a handful of countries, such as Australia and New Zealand, examine the impact of macroeconomic trends and government policies on the future evolution of government assets, liabilities, and net worth.

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**Table 12: Impact of Reform on Prices**

|(1)<br>Dependent variable: Lo|(2)<br> gconsumer price index|
|---|---|
|Reform dummy (SARE)<br>-0.0056<br>(0.0043)|-0.0058**<br>(0.0027)|
|Time span<br>Apr 00 - Dec 04|Apr 00 - May 06|
|R-squared<br>0.980|0.983|
|No. of observations<br>1,140|1,480|

_Note:_ Standard errors in parentheses (clustered at municipality level). Regressions include month and municipality fixed effects, as well as 1999 municipality log GDP per capita, log number of economic establishments per 1000 capita, log fixed assets per capita, and log investment per capita, all interacted with a linear time trend. Regressions are for 20 municipalities only since the price index is only available for 20 of the 34 municipalities in the main sample. Significance levels: * 10%, ** 5%, *** 1%

**Table 13: Impact of Reform on Prices by Subcategory**

|Dependent variable: Log Price index for|Coefficient on reform<br>dummy (SARE)|
|---|---|
|Non-tradables in low-risk industries|-0.0096**<br>(0.0040)|
|Non-tradables in high-risk industries|-0.0062<br>(0.0089)|
|Tradables in low-risk industries|-0.0039<br>(0.0034)|
|Tradables in high-risk industries|0.0014<br>(0.0036)|

_Note:_ Standard errors in parentheses (clustered at municipality level). Regressions include month and municipality fixed effects, as well as 1999 municipality log GDP per capita, log number of economic establishments per 1000 capita, log fixed assets per capita, and log investment per capita, all interacted with a linear time trend. Regressions are for 20 municipalities only since the price index is only available for 20 of the 34 municipalities in the main sample. Regressions are for the April 2000 to May 2006 time span and include 1,480 observations. Significance levels: * 10%, ** 5%, *** 1% 45
Nevis and St. Kitts), and St. Vincent & the Grenadines. These were routes with short distances and very low volumes with destinations that are now served by ferries or general aviation type charter flights.

# <u>Caribbean Hub Countries</u>

The Bahamas and Trinidad & Tobago stand out in the region because of their high volumes of domestic travel (Figures 11a and 11b). The Bahamas features 18 islands with a total of 64 airports and heliports, of which 12 have regularly scheduled services. There were three airlines in 2013 serving the domestic market, with the bulk of the market served by Southern Air Charters (57%), followed by Bahamas Air (26%, also the state owned flag carrier), and SkyBahamas (17%). Growth has been significant: between 2001 and 2013, capacity grew by 5.0% annually, and the recent five year annual growth rate, between 2008 and 2013 (following the economic slowdown), stood at 9.6%. The number of direct-flight airport pairs being served, however, has declined: the number of airports being served declined from a peak of 43 to 23 in 2013 (Figure 11a).

**Figure 11: Domestic travel in Hub Countries**

<!-- Start of picture text --> a. The Bahamas b. Trinidad and Tobago*<br> 1,600 50 1,200 3<br> 1,400 45<br> 40 1,000<br> 1,200<br> 35<br> 800 2<br> 1,000 30<br> 800 25 600<br> 600 20<br> 400 1<br> 15<br> 400<br> 10<br> 200<br> 200 5<br> - - - -<br>Estimated Seats Airport Pairs Estimated Seats Airport Pairs<br>c. Jamaica d. Dominican Republic<br> 1,000 10 200 10<br> 800 8 150 8<br> 600 6 6<br> 100<br>4<br> 400 4<br> 50<br>2<br> 200 2<br> - 0<br> - 0<br>Year<br>Year<br>Scheduled Seats Airport Pairs<br>Scheduled Seats Airport Pairs<br>Source: Authors’ calculation based on data provided by Diio (2014).<br>Estimated Seats, thousands Domestic Airport Pairs Served Estimated Seats, thousands Domsetic Airports Served<br>Estimated Seats, thoushadns Domestic Airports Served Domestic Airports Served<br>Estimated Seats, thousands<br><!-- End of picture text --> _Note: Trinidad and Tobago only has one airport pair, between the two islands._ The volume of traffic between Trinidad and Tobago is also quite high (Figure 11b). There is a single airport pair, served solely by Caribbean Airlines, Trinidad’s flag carrier. Long-term growth has been 6.0% 35
# **Figure 1a: Progress toward the health MDGs for the entire population**

<!-- Start of picture text --> Stunting Underweight IMR U5MR<br>0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1<br>Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a.<br>Full immunization Measles ANC4+ SBA<br>0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1<br>Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a.<br>Contraception HIV-prevalence HIV-condom Malaria-net children<br>0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1<br>Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a. Cumul. fraction of countries ranked by av. growth p.a.<br>.08 .1 .1 .08<br>.06 .08 .06<br>.04 .05 .06 .04<br>.04<br>.02 0 .02 .02<br>0 0<br>Av. growth p.a. -.02 Av. growth p.a. -.05 Av. growth p.a. 0-.02 Av. growth p.a. -.02<br>-.04 -.1 -.04 -.04<br>-.06 -.06 -.06<br>-.08 -.15 -.08 -.08<br>.4 .5 .7<br>.2<br>.6<br>.3 .4<br>.15 .5<br>.2 .3 .4<br>.1<br>.1 .2 .3<br>.05 .2<br>Av. growth p.a. 0 Av. growth p.a. Av. growth p.a. .1 Av. growth p.a.<br>0 .1<br>-.1 0 0<br>-.2 -.05 -.1 -.1<br>1.4 .01 .16 .6<br>1.2 0 .14 .5<br>1 -.01 .12 .4<br>.8 -.02 .1 .3<br>.2<br>.6 -.03 .08<br>.1<br>.4 -.04 .06 0<br>Av. growth p.a. .2 Av. growth p.a. -.05 Av. growth p.a. .04 Av. growth p.a. -.1<br>0 -.06 .02 -.2<br>-.2 -.07 0 -.3<br>-.4 -.08 -.02 -.4<br><!-- End of picture text --> Source: Authors’ calculations from original DHS and MICS datasets. The annual growth is as a fraction, so e.g. 0.02 means 2% annual growth.

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(i.e., the native population) and an out-group (i.e., the refugees) reduces prejudice if the following features characterise the contact situation: firstly, _equal status_ of the groups in the situation, which means that the two groups are equally engaged in the relationship and ideally have similar backgrounds and characteristics. Secondly, the groups work together on _common goals_ , which should not be achieved in competition but rather in _intergroup cooperation_ . Thirdly, _personal interaction_ with cross-group members. Lastly, _support of authorities_ , law, or custom.

This paper contributes to this extensive literature by highlighting the important role of resettlement policies in creating favourable conditions for positive intergroup contact. By providing refugees with farmland and making the self-sufficient, the League of Nations reduced the competition with natives in the labor market. By opening new schools, constructing new roads and dispensaries, the Leagues’ public utility program further helped mitigate the risk of congestion and overcrowding caused by the sudden refugee inflow. Granting the citizenship also contributed to equal status between the newcomers and the locals.

# **4 Research Design**

## **4.1 Data**

### **4.1.1 Historical data on the refugees**

The primary data source to identify the spatial distribution of the refugee inflow is the 1928 population census.<sup>15</sup> This dataset provides information on the number of refugees for reach of the 140 provinces and 5,042 municipalities that existed in Greece in 1928. While the main variable of interest is the population share of refugees in 1928, I also draw on the 1923 refugee census at the municipality level to check the robustness of the analysis to using the distribution of refugees in 1923.<sup>16</sup> The 1928 census provides a rich set of information on the socio-economic characteristics, e.g., literacy rate by age and professions, of the total Greek population and of the refugees separately. It also tabulates the characteristics of the population in 1920 for comparison. However, these information are available only at the province level level.

According to the refugee census, 778,000 refugees arrived in Greece in April 1923. After the population exchange, their number rose up to 1.07 million in 1928, accounting for 16.6 percent of the total population (out of 6.08 million). 53.9% of refugees settled in urban areas, while only 30% of Greek natives lived in cities in 1928. The three biggest cities in Greece, Athens, Piraeus, and Thessaloniki, hosted about half of the urban refugees. I exclude these three cities from the

> 15See Figure A.2 in the Appendix for the questionnaire (bulletin) and an example of historical table.

> 16This census was taken in April 1923, after the mass inflow of refugees but before the Lausanne Peace Treaty and the agreement on the forced population exchange between the Kingdom of Greece and Turkey. Figure A.1 in Supplementary Appendix presents the timeline of events that are relevant for the settlement and enumeration of refugees.

10
# Table 7 Heavily Indebted Countries: Implicit Debt Overhang Tax Rate

||(in pe<br>|rcent)<br>|||
|---|---|---|---|---|
|Values of (r-n)|7.00|5.00|3.00|1.00|
|Argentina<br>|3.09<br>|2.21<br>|1.32<br>|0.44<br>|
|Bolivia<br>|6.57<br>|4.70<br>|2.82<br>|0.94<br>|
|Brazil<br>|1.26<br>|0.90<br>|0.54<br>|0.18<br>|
|Chile<br>|2.40<br>|1.71<br>|1.03<br>|0.34<br>|
|Cote d' Ivoire<br>|6.65<br>|4.75<br>|2.85<br>|0.95<br>|
|Ecuador<br>|5.97<br>|4.27<br>|2.56<br>|0.85<br>|
|Mexico<br>|2.07<br>|1.48<br>|0.89<br>|0.30<br>|
|Morocco<br>|3.39<br>|2.42<br>|1.45<br>|0.48<br>|
|Peru<br>|5.09<br>|3.63<br>|2.18<br>|0.73<br>|
|Philippines<br>|2.20<br>|1.57<br>|0.94<br>|0.31<br>|
|Uruguay<br>|1.17<br>|0.84<br>|0.50<br>|0.17<br>|
|Venezuela|2.09|1.49|0.90|0.30|

Source: Underlying data were provided by the World Bank. Calculations are described in the text.
<u>Table 4: Piecewise Regression for Annual Remittances</u>

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Migrant's annual earnings (US$)|0.255***|0.547***|0.527***|0.527***|
||(0.08)|(0.15)|(0.12)|(0.13)|
|Migrant's annual earnings beyond income threshold (US$)||-0.455*<br>(0.25)|-0.438**<br>(0.22)|-0.425*<br>(0.22)|
|No. of other household members working abroad|||-1,556***<br>(348)|-1,670***<br>(350)|
|Hhold annual medical expenditure as a share of income|||3,506***<br>(1263)|3,374**<br>(1299)|
|Log household's annual income in India|||122.3**<br>(55.6)|81.87<br>(72.4)|
|Median monthly income of Gulf migrants (log)|||1,994***<br>(651.7)|2,112***<br>(707.8)|
|Additional controls|No|No|No|Yes|
|R-square|0.15|0.19|0.41|0.44|
|Number of observations|108|108|108|108|

Notes: Additional controls consist of the wife's years of education and indicators for whether the wife is employed, unaware of her husband's expenses, having disagreements over remittance uses, and if the migrant spends on temptation goods. All regression includes a constant term. Bootstrapped standard errors (with 500 replications) are displayed in parenthesis, clustered at the district level. The threshold income of USD 6,740 was determined using a non-linear least square method using all variables in column (4).

*** denotes statistical significance at the 1% level, ** at the 5% level and * at the 10% level. _Source:_ Authors’ analysis based on data from QSKF.

From column 4 in table 4, we observe that, all else equal, that is, for the “representative household,” remittances increase on average by US$ 0.53 for every dollar increase in income below the threshold of US$ 6,740. However, past the threshold, transfers increase only by US$ 0.11.<sup>22</sup> Thus, consistent with the model’s prediction, the slope of the remittance function is smaller beyond the threshold. This pattern of remitting behavior is similar to the threshold reporting behavior as discussed in relationship to figure 2.<sup>23</sup> 22. A potential concern is that these results may not be robust due to the limited number of observations beyond the threshold of US$ 6,740 (which is about 28% of all the observations). We also tested the robustness of the change in slopes using the median level of annual income of US$5,918 as the threshold. Annual remittances rose by US$0.57 for every dollar below the threshold and US$0.16 for each dollar of income above it.

23. Joseph et al. (2015) using matched administrative data on remittance and earnings data for a panel of U.A.E. migrants find that remittances are unresponsive to increases in income over time but fall with negative income shocks, consistent with the empirical pattern we find.

29
visible in Ghana and Uganda, where its introduction was contentious, and where recurrent political debate about VAT rates suggests that its political effect has been quite direct (OECD 2008).

Therefore, in our second step, we test if the share of various taxes has an impact on accountability vis-à-vis citizens. The greater is the share of taxes on trade (the least visible type of tax, and a narrower tax base), the less accountable the government is likely to be. Moreover, due to the fact that in oil economies, revenue from taxes are minimal, we can expect that controlling for the impact of various taxes, a greater dependency on oil is likely to create less accountability.

For this second step, we depart from Shah’s (2005) specification by controlling for a country’s level of development (GDP per capita) and overall policy framework (trade openness ratio). We test whether variables capturing the dependence on various types of taxes as well as oil dependency are significantly associated with accountability. In this second step, we keep the same measure of voice and accountability.

Table 4 gives the results of this second step. We use two measures of oil dependency. In specification 1, we use the share of oil exports in total exports and in the second one, we use the share oil exports in GDP from the World Development Indicators database. In both cases, controlling for development and policy variables, it appears that oil dependency has a negative association with accountability<sup>9</sup> . This confirms what is alluded to in the literature on the resource curse.

But what is striking is that, for countries relying on income taxes of individuals (measured as a share of total taxes), accountability is much higher (controlling for the same variables). By contrast, for countries relying on trade taxes, which can be associated with rents in some countries, accountability is lower (although the coefficient is not strongly significant). It is also worth noting that controlling for all

> 9 This is also consistent with findings from Heuty et al. (2009).

11
# **<u>Table A2: Effect of computerization on credit supply in subset of SROs</u>**

||**Depen**|**dent variable:**|**log of credit**|**disbursed by**|**banks**|
|---|---|---|---|---|---|
|Computerization|1.053|0.62|-0.003|-0.012||
||[0.015]**|[0.020]**|[0.013]|[0.013]||
|Comp*Urban Share||||0.143<br>[0.052]**||
|Post0_4 Quarters|||||-0.005|
||||||[0.014]|
|Post 5+Quarters|||||-0.015<br>[0.017]|
|Post0_4 Quarters*Urban Share|||||0.058<br>[0.033]*|
|Post 5+Quarters*Urban Share|||||0.167<br>[0.060]**|
|Quarter*Year Fixed Effects|No|Yes|Yes|Yes|Yes|
|_Taluk_Fixed Effects|No|No|Yes|Yes|Yes|
|Observations|30,025|30,025|30,025|30,025|30,025|
|R-squared|0.14|0.21|0.97|0.97|0.97|

Notes: _Taluk_ and year*quarter fixed effects included throughout. Robust standard errors clustered at the _taluk_ level. * significant at 5%; ** significant at 1% 22
<!-- Start of picture text --> 25<br>20<br>~ 15 ————= share oftotal<br>5 , “nt government<br>a.2 eo;: expenditurei to GDP<br>10 ~ \ __-? beled ----GDP growth rate<br>——_-<br>5<br>0<br>® 5 & © ae & © &<br>PPoO PD PS PS SF SS‘Yy<br><!-- End of picture text -->
# Technology Within and Across Firms<sup>_∗_</sup>

Xavier Cirera Diego Comin Marcio Cruz Kyung Min Lee World Bank Dartmouth College World Bank World Bank

## **JEL Codes:** D2, E23, L23, O10, O40

## **Keywords:** Technology, Firms, Productivity

> _∗_ We thank Bill Maloney, Caroline Freund, Najy Benhassine, Denis Medvedev, Mary Hallward-Driemeier, Paulo Correa, Mark Dutz, Ana Margarida Fernandes, Leonardo Iacovone, Jorge Meza, Silvia Muzi, Doug Staiger, and participants at seminars at the World Bank, Innovation Growth Lab Conference, and Dartmouth College for comments and feedback on the survey questionnaire, as well as on earlier drafts of the paper. We especially thank Jo ̃ao Belivaqua Basto, Tanay Balantrapu, and Carmen Contreras for their help through the data collection and preparation of the questionnaire, as well as the inputs from several external sector and production experts (an extended list of sector experts is provided in the appendix). We also thank the National Agency of Statistics and Demography of Senegal (ANSD), the Federation of Industries of the State of Cear ́a (FIEC), and the General Statistics Office of Vietnam (GSO) for their partnership in implementing the survey. Financial support from the Korea World Bank Group Partnership Facility (KWPF) and the Competitive Industries and Innovation Program (CIIP) for data collection is gratefully acknowledged. The views expressed in this paper are solely those of the authors and do not necessarily reflect those of the World Bank or its Board.
Policy Research Working Paper 11031

# **Abstract**

This paper examines the dynamics of poverty in Bhutan between 2017 and 2022, utilizing cross-sectional data from the Bhutan Living Standards Surveys. The paper constructs synthetic panels and estimates poverty transition probabilities. Three main findings emerge. First, poverty turnover in Bhutan is low overall (not many people, as a share of the population, moved in and out of poverty during the period considered). Second, chronic poverty, defined as the probability of remaining poor in both years (2017 and 2022), was also low, both in absolute terms and compared to other countries for which similar estimates are available. The probability of being poor in both years is 6 percent of households in Bhutan, compared to over 15 percent in India and 17.5 percent in Pakistan. Third, upward poverty mobility (the probability of escaping poverty between 2017 and 2022) is 20 times higher than downward poverty mobility.

This paper is a product of the Poverty and Equity Global Department. 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://www.worldbank.org/prwp. The authors may be contacted at aetangndip@worldbank.org; nicola.amendola@uniroma2.it; federico.belotti@uniroma2.it; giulia.mancini@uniroma2.it; and giovanni.vecchi@uniroma2.it.

_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
||**Tab**|**le**1|:**Im**|**pact**|of policy<br>on bank|beha|vior||||
|---|---|---|---|---|---|---|---|---|---|---|
|||I|NTER|IOR|||C|ORNE|R||
||x,n|_a_|rD|_d_|_D_<br>_Bonds_<br>|_x,n_|a|rD|_d_|_D_|
||_7+t_|0|<br>0|-|0<br>-|+|0|<br>+|+|+|
|As (W')|0|0|+|+|+<br>+|+|0|+|+|+|
|_rot_|0|0|<br>+|+|+<br>+|0|0|<br>0|0|0|
||0|0|+|+|+<br>+|0|0|-|-|-|
||0|0|+|+|+<br>+|0|0|0|0|0|
||+|0|0|-|0<br>-|+|0|+|4|+|
|_r"t_|-|0|<br>+|+|+<br>+|+|0|<br>+|+|+|
|rt|-|0|<br>+|+|+<br>+|+|0|<br>0|0|0|
||-|0|.|.|.<br>+|+|0|-|||
||-|0|<br>+|+|+<br>+|+|0|<br>+|+|.|

*Assumes low values of .

63