rafmacalaba/data-use-mentions-extended huggingface dataset:
expenditure on housing, which amounts to 60-65% of the total budgeted subsidies. The inefficient system of subsidy allocation combined with the lack of metering of utility services and with poor corporate governance and regulation of utility companies lead to the accumulation of enornous efficiency losses in the housing sector. Energy consumption in a typical Russian apartnent building is 2-3 times higher than in market economies with comparable climatic conditions (Martinot, 1997). Wealthier households tend to have larger apartments and, thus, receive more in housing subsidies.

# m. **Comments on the** Data: **Peculiarities of Major Indicators, Availability, Sources**

The Russian budget reporting system does not provide statistically accurate data on budgeted subsidies as a part of the overall budget spending. The budget classification in use before 1995 was based on principles quite different from those since put in place. The old classification was basically the traditional Soviet classification with small modifications and it was focused on the aggregated sectoral breakdown of total expenditures. And the data on regional spending collected by the federal Ministry of Finance did not provide sufficient information to build a detailed functional classification of budget expenditure (Freinkman and Titov, 1994). The new budget classification introduced in 1995 is based on internationally recognized principles, and, when fully implemented, will fill this informational gap. However, at the time this paper was 8 Through cash allowance or food stamp types of instruments. 9 In particular, actual beneficiaries of livestock subsidies are firms in procurement and meat processing but not livestock producers (Serova and Melyukhina, 1995).
respond to contemporaneous shocks.

**Figure 2: Disbursement rates over the life of a loan**

A. Average disbursement rate B. Average disbursement rate, by creditor type <!-- Start of picture text --> Share of loan disbursed Share of loan disbursed<br>0.16 0.18<br>0.14 0.16 Multilateral loans<br>0.12 0.14 Bilateral loans<br>0.12<br>0.10<br>0.10<br>0.08<br>0.08<br>0.06<br>0.06<br>0.04 0.04<br>0.02 0.02<br>0.00 0.00<br>t t+1 t+2 t+3 t+4 t+5 t+6 t+7 t+8 t+9 t+10 t t+1 t+2 t+3 t+4 t+5 t+6 t+7 t+8 t+9 t+10<br><!-- End of picture text --> _Source:_ Authors’ calculations.

_Note:_ Based on average disbursement rates for 73,994 loans (32,965 for multilateral and 41,029 for bilateral) in year of loan and subsequent years.

Since the predicted disbursements are in current US$, to get our instrumental variable relative to GDP, we convert it to local currency using exchange rates from the World Bank’s World Development Indicators, then deflate using the GDP deflator and again divide it by lagged real GDP. Before running regressions, we remove the 1<sup>st</sup> and 99<sup>th</sup> percentiles of each variable. After constructing our variables, we have observations between 1980 and 2019 for our regressions. Table 1 provides summary statistics of the main variables of interest
<br>‐1.00 ‐0.75 ‐0.50 ‐0.25 0.00 0.25 0.50 0.75 1.00<br><!-- End of picture text --> _Source:_ Egypt: based on HIECS 2015 and budget figures. All others: - de la Fuente, Jellema and Lustig 2018. _Note:_ Hospital/inpatient health in Egypt includes outpatient services at public hospitals.

The fiscal gains to the poor effectiveness indicator (Figure 18) provides a similarly intuitive statistic for the effectiveness of direct and indirect transfers in protecting poor and vulnerable households from further impoverishment. In other words, the Karama direct cash transfer was the most effective at protecting poor households _specifically_ because it was targeted to households in the poorest 20 percent of the population. The Takaful program, meanwhile, delivered far greater amounts through direct transfers, but it delivered

> 51 With such “sin taxes” Egypt may create incentives for better long-term public health outcomes and therefore long-term increases in human capital and incomes in all households and thereby also long-term reductions in income inequality (see for example Fuchs, Hasbun, and Mukong 2018). Such long-term dynamics are not captured here.

35
of picture text --> Source: ECB and Federal Reserve Bank of St. Louis.

Weekly data. FED: FED, Federal funds (effective) rate ECB: ECB, Main refinancing operations interest rate BoJ: Bank of Japan, Basic discount rate and basic loan rate BoE: Bank of England, Official bank rate Source: FED, ECB, BoJ, BoE.

# **Lesson 7: Monetary policy is only as good as the transmission mechanism.**

_<u>As growth recovery struggled, debates surrounding the effectiveness of different types of monetary instruments and the desired</u> “looseness” of policy abounded. Over time, the ECB’s policies_ _<u>became looser, but were hindered from having a commensurate effect because of structural features of financial markets and/or incomplete restructuring of balance sheets among firms, households and banks.</u>_ Monetary policy is transmitted through the financial system to borrowers and thus its ability to stimulate demand and manage inflation depends on the structure and incentives in the financial system as well as in the economy at large (firms and households). Structural factors in the financial system include the degree of market competition, the extent of information asymmetries present, volatility and uncertainty, credit risk in the economy, or on the consumer side, costs for bank switching.<sup>55</sup> They also include changes in household preferences or the financial health of borrowers, expectations of global demand and government finances. For example, in a study of interest rate pass through in Portugal, Rocha (2012) finds that there is incomplete long run pass‐through from interbank rates (an indicator of the monetary policy stance) to corporate lending rates in the long run. The ECB, studying the four largest euro area countries, France, Germany, Italy and Spain, has also found that policy rate cuts since late 2011 have broadly lowered interest rates to NFCs in France and Germany, but the pass‐ through
identified, we impute the average expenditure per student of the corresponding level as an in-kind transfer for each of them.

- _Health_ **_._** Using the PNS survey, we identify the usage of public health services by age and sex in five categories: (i) curative attention, (ii) dental care, (iii) rehabilitation, (iv) medicines (covered by the government), laboratory exams and (v) other diagnostics. These are the categories for which the Brazilian Ministry of Health publishes detailed information on the total public expenditure per type of health service (Brazil, 2022a). Currently, 2019 is the latest year for which such information is available. Given that PNAD-C does not have questions about usage of public health services, we resort to an alternative approach to impute in-kind health transfers to the population. It involves randomly selecting some individuals in PNAD-C to set them as fictitious users of public health services and then impute the average public expenditure per patient as an in-kind health transfer to them. The number of individuals set as fictitious beneficiaries in PNAD-C is determined so as to mimic the actual usage of public health services by age and sex according to PNS data. 28F<sup>29</sup> To calculate the average public expenditure per patient, we use information on the total expenditure from the Ministry of Health and calculate the population-weighted number of fictitious beneficiaries in PNAD-C data.  Since the data on total public expenditure per patient is disaggregated into the aforementioned five categories (i.e, curative attention, dental, rehabilitation, etc.), this procedure is carried out separately for each of them.

Finally, we present in Table 2 the list of public transfers, contributory pensions and other social spending items in Brazil relative to 2019 and their corresponding share in both the total government expenditure and GDP. The table also indicates the expenditure items considered in our fiscal incidence analysis. We see that total expenditure accounts for 49.3% of the GDP and that social spending
Figure A.5 Regional Level Improved Sanitation Deprivation a) b) <!-- Start of picture text --> Urban Improved Sanitation Deprivation - Rural Improved Sanitation Deprivation - Geopolitical<br>Geopolitical Zone - GHS Zone - GHS<br>80% 80%<br>70% 70%<br>60% 60%<br>50% 50%<br>40% 40%<br>30% 30%<br>20% 20%<br>10% 10%<br>0% 0%<br>Wave 1_NC Wave 2_NC Wave 3_NC Wave 4_NC<br>Wave 1_NC Wave 2_NC Wave 3_NC Wave 4_NC<br>Wave 1_NE Wave 2_NE Wave 3_NE Wave 4_NE<br>Wave 1_NE Wave 2_NE Wave 3_NE Wave 4_NE<br>Wave 1_NW Wave 2_NW Wave 3_NW Wave 4_NW<br>Wave 1_NW Wave 2_NW Wave 3_NW Wave 4_NW<br>Wave 1_SE Wave 2_SE Wave 3_SE Wave 4_SE Wave 1_SE Wave 2_SE Wave 3_SE Wave 4_SE<br>Wave 1_SS Wave 2_SS Wave 3_SS Wave 4_SS Wave 1_SS Wave 2_SS Wave 3_SS Wave 4_SS<br>Wave 1_SW Wave 2_SW Wave 3_SW Wave 4_SW Wave 1_SW Wave 2_SW Wave 3_SW Wave 4_SW<br><!-- End of picture text --> Source: Authors’ estimates based on GHS Wave 1-4 Note: Individuals with missing age were dropped from the analysis. Estimations are based in children aged 0-17.

<!-- Start of picture text --> Figure A.6: State Level Improved Sanitation Deprivation by Region<br>a) b) c)<br>Improved Sanitation Deprivation - Improved Sanitation Deprivation - Improved Sanitation Deprivation -<br>by State in North Central - MICS by State in North East - MICS by State in North West- MICS<br>80% 80% 80%<br>70% 70% 70%<br>60% 60% 60%<br>50% 50% 50%<br
and Loayza (2005) rule Rule of Law index. Source: Kaufmann, Kraay, and Zoido-Lobatón (2002) lpats_pop Log (patents granted in the U.S. and Europe/ total population). Sources: USPTO, EPO, and World Bank. lmort Log (settler mortality). Source: Acemoglu, Johnson, and Robinson (2001) lip Log (average IP index 1960-1995). Source: Park and Ginarte (2001) Fraction of population speaking one of the major languages of Western Europe: English, French, German, eurfrac Portuguese, or Spanish. Source: Hall and Jones(1999). oilprueba2 Dummy variable taking value of 1 if country is net exporter of oil. cen_latabs Absolute value for country centroid latitude. landlock Dummy variable taking value of 1 lacks of access to the sea. ssa Dummy variable taking value of 1 if country is located in Sub-Saharan Africa. lcts Log (Constructed Trade Share). Source: Frankel and Romer (1999). malfal94 Malaria Index, year 1994. Source: Gallup and Sachs (1998).

31
countries but within industries. If industry characteristics affect the results, then the panel and pooled estimates will be quite different, and the factor endowments perspective will be shown to contribute to our understanding of discovery. The results using both HS 4-digit and HS 6-Digit data are shown in Table 6.

**<u>Table 6: Testing for Structural Transformation</u>**

||**HS 4**<br>|**-Digit**<br>|**HS 6**<br>|**-Digit**<br>|
|---|---|---|---|---|
||**Discoveries by**<br>**Industry**|**Discoveries**<br>**Pooled**|**Discoveries by**<br>**Industry**|**Discoveries**<br>**Pooled**|
|Coefficient on ln<br>GDPpercapita|13.5666<br>(7.02)|15.6518<br>(5.68)|11.9700<br>(9.56)|15.7203<br>(5.89)|
|95% Confidence<br>Interval|<br>9.7769 to<br>17.3562|10.2503 to<br>21.0532|9.5152 to<br>14.4248|10.4869 to<br>20.9535|
|Coefficient on ln|-.8109|-.92803|-.6970|-.9114|
|GDP per capita<br>squared|(-7.29)|(-5.92)|(-9.83)|(-6.03)|
|95% Confidence<br>Interval|-1.02 to -.5929
Openness in a Crisis-Prone World Market: a Nuanced View”, _NBER Working Paper_ , no. 10555.

- Reinhart, C. M. and K. Rogoff (2002), “The Modern History of Exchange Rate Arrangements: a Reintepretation”, _NBER Working Paper_ , no. 8963.

- Strand, H., L. Wilhelmsen and N. P. Gleditsch (2004), “Armed Conflict Dataset Codebook (version 3.0)”, mimeo.

- Woodruff, C. and R. Zenteno (2004), “Remittances and Microenterprises in Mexico”, _Graduate School of International Relations and Pacific Studies Working Paper_ (University of San Diego).

- Yang, D. (2005), “International Migration, Human Capital, and Entrepreneurship: Evidence form Philippine Migrants’ Exchange Rate Shocks”, _Policy Research Working Paper_ , no. 3578, Research Program on International Migration and Development, International Trade Unit, Development Economics Research Group, World Bank.
a similar pattern, albeit, less clearly. The relatively subtle indications of spatial dependence suggested in the kernels emerge as statistically significant in the Moran test, most notably, consistent with the kernels above, in the bands measure that most clearly captures the border and southern concentrations of wealth and poverty.

The local Moran statistics identify whether particular groupings of states co-vary in a statistically significant way and largely confirm the observations from the kernels. We present them in several different formats. First, the maps in figures 6a and 6b show the geographical distribution of significant local Morans based on contiguity for both the 10% 13
impractical to analyze macroprudential policy in isolation, we also jointly analyze the macroeconomic effects of the central bank policy interest rate (IR, hereafter) on the macroeconomy. To properly identify exogenous IR shocks, we follow Romer and Romer’s (2004) approach and purge the policy rate from systematic responses to information about future economic developments. Given the time-consuming efforts needed to carry out the analysis along these several critical dimensions, we focus our analysis on three Latin American countries (Argentina, Brazil, and Uruguay) since the early 1990s.

The paper proceeds as follows. Section 2 describes the novel RR dataset and some broad features of the data. Section 3 shows empirical evidence on the macroeconomic effects of macroprudential and monetary policies relying on traditional time-identifying assumptions. In line with the predictions of any standard macro model, we find a negative effect of central

> 7For example, as will be discussed later in the paper, while total banks’ reserves may fluctuate due to non-policy factors (including the structure of deposits), RR changes due to central bank policy take place, on average, every 2 years in developing and emerging markets.

4
- González, R. M., Marrero, G. A., Rodríguez-López, J., & Marrero, Á. S. (2019). Analyzing CO2 emissions from passenger cars in Europe: A dynamic panel data approach. _Energy Policy_ , _129_ , 1271–1281. https://doi.org/10.1016/j.enpol.2019.03.031

- Hang, Y., Wang, Q., Zhou, D., & Zhang, L. (2019). Factors influencing the progress in decoupling economic growth from carbon dioxide emissions in China’s manufacturing industry. _Resources, Conservation and Recycling_ , _146_ , 77–88. https://doi.org/10.1016/J.RESCONREC.2019.03.034

- Huang, Y., Zhu, H., & Zhang, Z. (2020). The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: Evidence from dynamic panel quantile regression. _Science of The Total Environment_ , _727_ , 138578. https://doi.org/10.1016/J.SCITOTENV.2020.138578

- Huo, T., Ma, Y., Yu, T., Cai, W., Liu, B., & Ren, H. (2021). Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China. _Environmental Impact Assessment Review_ , _86_ , 106487. https://doi.org/10.1016/J.EIAR.2020.106487

IEA. (2020). _Energy Technology Perspectives 2020_ . www.iea.org/t&c/

- IPCC, Edenhofer, O., Sokona, Y., Minx, J. C., Farahani, E., Kadner, S., Seyboth, K., Adler, A., Baum, I., Brunner, S., Kriemann, B.
, cocoa, spices (SITC 07). The respondents are also asked to identify the likely port of loading (Djankov et al., 2010). Therefore, the variation in transport costs across products, routes, or firms is rather limited (Blonigen and Wilson, 2018). The advantage of these data is that it allows for a comparison across many countries and some variation over time in the cost of a container and provides a more accurate measure of transport costs than, for example, the previously discussed c.i.f over f.o.b ratio or physical distance.

Finally, some studies use more focused data. For example, Simonovska (2015) used the DHL shipping rates, Limao and Venables (2001) used shipping rate quotes for a standard 20-container from

> 18The survey has been recently discontinued. See WB Statement for more details.

20
Coefficient Std. Err.

Table 9: ELL household (log) consumption regression model

||Coefcient|Std. Err.|
|---|---|---|
|Intercept|-4.3293|(0.0726)|
|STRATA<br>1|0.0265|(0.1417)|
|STRATA<br>2|-0.2575|(0.1435)|
|STRATA<br>3|-0.2739|(0.1332)|
|STRATA<br>4|0.2134|(0.0946)|
|STRATA<br>5|0.2481|(0.064)|
|TA<br>REMOTE100K|-0.062|(0.0262)|

Table 10: ELL heteroskedasticity model

# **References**

- Alderman, H., Babita, M., Demombynes, G., Makhatha, N. and Ozler, B.<sup> ̈</sup> (2002). How low can you go? combining census and survey data for mapping poverty in south africa. _Journal of African Economies_ , **11,** number 2, 169–200.

- Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998). Crop evapotranspirationguidelines for computing crop water requirements. Irrigation and drainage paper 56. FAO, Rome.

- Anselin, L. (2001). _Spatial econometrics_ , A companion to theoretical econometrics, 310330 edn.

- Araujo, M., Ferreira, F., Lanjouw, P. and Ozler, B. (2008). Local inequality and project choice: Theory and evidence from ecuador. _Journal of Public Economics_ , **92,** 1022–1046.

- Aubrecht, C., Gunasekera, R., Ungar, J. and Ishizawa, O. (2016).
ideals in eighteenth century Europe emphasized objective scientific inquiry. The role of data evolved to a means of examining society and became more public. In the late eighteenth century, statistical agencies were set up in Europe and North America to publish official statistics and inform the public.

> 1 The World Uncertain Index developed by Ahir, Bloom, and Furceri (2022) has an average score of 19,553 between 2005 and 2018 in contrast to a score of 12,829 between 1990 and 2004.

3
7 in total), thereby</sup> excluding the mostly smaller regional banks (127 in total).<sup>To limit the large number of</sup> listed banks in the US, we only include the 22 largest<sup>US banks, namely the multinational</sup> banks (6 in total) and the super regional banks (16 in total) as defined<sup>by Goldman Sachs.</sup> For the 137 banks we have collected a total of 917 observations<sup>across eight years.</sup> Data is missing for 179 observations for a number of<sup>reasons. Some banks have not</sup> reported accounting data for each year, some banks only listed<sup>at a certain point in the</sup> sample period, and some banks were de-listed during<sup>the sample period, because of</sup> government intervention or merger activity.<sup>5</sup> Missing observations<sup>for the year 1998 are</sup> 4 The distribution of the number of banks across countries is as follows (with the number of banks between brackets): France (4), Germany (8), Hong Kong (12), Indonesia<sup>(8), Japan (19), Korea (22), Malaysia (10),</sup> Singapore (5), Taiwan (8), Thailand (12), United Kingdom (7), US (22).

5 In Indonesia, Bank Tiara Asia, a private foreign exchange bank,<sup>was taken over in 1998 by the Indonesian</sup> Bank Restructuring Agency and is therefore missing for 1998. Although Indonesian<sup>Bank Danamon</sup> merged with state-owned bank PDCFI in 1998, both banks continued<sup>reporting separately for another year,</sup> so that we could include Bank Danamon's
that the productivity impact of IT is substantially larger than its cost share (e.g. Bresnahan, Brynjolfsson and Hitt, 2002). The literature argues this is because IT is complementary with modern management and organizational practices, so that as firms invest in IT they also improve their management practices. This leads to a positive bias on IT in productivity estimates because management and organizational practices are typically an unmeasured residual.<sup>24</sup> But none of this literature has any experimental evidence.

So to investigate the potential complementarity between IT and management practices we collected computerization data on nine aspects of the plants, covering the use of Enterprise Resource Planning (ERP) systems, the number of computers, the age of the computers, the number of computer users, the total hours of computer use, the connection of the plant to the

> 24 See, for example, Bartel, Ichniowski and Shaw (2007) and Bloom, Sadun and van Reenen (2009a).

22
the average extreme poverty rate for countries with nominal GDP within 10 percent of PNG’s was approximately one-half of that reported in PNG- 21.2 percent.<sup>2</sup> Furthermore, many question the suitability of global well-being measures in PNG, and often refer to the term “subsistence affluence” to describe how community-level support and subsistence agriculture provide basic needs (e.g., Bourke 2000; Cammack 2007; etc.).

Given the substantial ambiguity regarding the extent of deprivation in the country and the degree to which it has changed in the past decade and a half, we aim to update key well-being estimates using the 2016-2018 Demographic and Health Survey (DHS). Specifically, we estimate the prevalence of monetary poverty in the country by tracking the change in close correlates of monetary poverty and imputing the poverty level using the relationship between those variables and poverty in the last official estimate. And we estimate the World Bank’s Multidimensional Poverty Measure (MPM), which is an index that combines information on access to critical and basic services and monetary poverty.

The data illustrate three clear patterns. First, despite growth in real per capita GDP of 29 percent and the other changes that have occurred between 2009 and 2016-2018, there was no change in the share estimated to be monetarily poor. The close correlates of poverty hardly changed over that time and the imputed share of the population living below the World Bank’s international poverty line of $ 2.15 (2017 PPP) in 2016-2018 was 39.3 percent, which is nearly identical to the estimate in 2009.<sup>3</sup> Additionally, poor access to essential services also changed very little from their initial low base. The changes were precisely estimated, and a significant improvement (or worsening) in any individual well-being measure analyzed here can be rejected at conventional significance levels.

Second, this lack of change in several key well-being measures is in contrast to the substantial monetary and non-monetary gains made in