rafmacalaba/datause-encoder-data huggingface dataset:
permanent basis, such current fiscal allocation rule for the reserve fund and future generations fund could usefully be complemented by an **_additional rule for non-oil primary fiscal deficit_** . The World Bank’s Fiscal Sustainability Analysis tool (FSA) presented in the annex is designed to analyze the interaction between these two rules (oil fund allocation rule and non-oil primary deficit rule).

**_The other macro issue--exchange rate management in oil-rich countries--has attracted considerable research and policy attention._** The first observation is that high spending unavoidably falls to a large extent on goods and services where international trade offers only an imperfect substitute, or none at all, such as construction. This, in turn, implies that high spending inevitably puts upward pressure on the prices of those goods and services, with a real appreciation as a result. For given expenditure levels, therefore, the authorities have no choice on the real exchange rate consequences, only on _how_ they come about. This depends in large part on the nature of the monetary-exchange regime. One option is a gradual revaluation of the nominal exchange rate, so as to effect the required real appreciation. If that option is not chosen, domestic goods end up underpriced given the state of demand for them, and high inflation will result, the other way of effecting a real appreciation. It is important to realize that such inflationary pressures are essentially fiscal in nature, related to expansionary fiscal policy; monetary tightening will mostly not be an appropriate response in this environment.

**_Real appreciation, unavoidable or not, always raises the issue of competitiveness and the survival of traditional manufacturing industries._** Key is to point out that such diversification concerns are appropriate only when the appreciation is expected to be temporary. But in countries like Russia, where oil income is likely to last for a century or more, a real appreciation in line with increased but sustainable expenditure levels does not call for specific support to industries in traded sectors; that will only result in open ended subsidy programs which in fact, when having any effect, will lead to further pressure on the real exchange rate.

In this paper we argue that: _In the long-term:_

- (1) The _permanent income_ (PI) approach to spending out of oil wealth provides a long-term solution to the problems mentioned.

- (2) By choosing a spending level that can be maintained indefinitely in real terms (which is what the PI approach amounts to), future generations share in the oil wealth.

- (3) A constant level of spending (in real terms) greatly reduces the volatility of government expenditure, thereby reducing the problems created by the volatility of oil revenues.

- (4) Since at the PI level spending can be maintained forever, there is no such thing as the post-oil economy; oil income is saved initially and its spending is spread out over the entire future period, in perpetuity.

5
# Appendix Chart 3 Characteristics of Different Types of Tightening Periods

Highly Synchronized Tightening Periods, the 2022 Highly Synchronized Tightening Period, and Other Tightening Phases <!-- Start of picture text --> Duration Number of Rate Hikes<br>90 30<br>60 20<br>30 10<br>0 0<br>Pre-2022 Highly 2022 Synchronized Other Tightening Pre-2022 Highly 2022 Synchronized Other Tightening<br>Synchronized Tightening Phases Synchronized Tightening Phases<br>Tightening Tightening<br>Average Pace Initial Velocity<br>3 3<br>2 2<br>1 1<br>0 0<br>Pre-2022 Highly 2022 Synchronized Other Tightening Pre-2022 Highly 2022 Synchronized Other Tightening<br>Synchronized Tightening Phases Synchronized Tightening Phases<br>Tightening Tightening<br>Amplitude (total rate change)<br>20<br>15<br>Range (10 - 90 percentile)<br>10 Mean<br>Median<br>5<br>0<br>Pre-2022 Highly 2022 Synchronized Other Tightening<br>Synchronized Tightening Phases<br>Tightening<br>Number<br>Rate change over first 6 months (in pp)<br>Months<br>Rate change per hike (in pp)<br>Total rate change (in pp)<br><!-- End of picture text --> Sources: Authors’ calculations based on the cycle dating methodology described in Section II. Data from January 1970 to May 2024.

Notes: Highly Synchronized Tightening periods are when at least 60% of the sample is in a tightening phase and at least 60% of the sample is increasing policy interest rates in the quarter. The 2022 Highly Synchronized Tightening is reported separately. “Other Tightening Phases” are tightening phases not included in these first two groups. See Section III for variable definitions.

85
# **<u>Appendix S3: Effects of Cash incentives</u>**

|Dependent variable:<br>|Received<br>|vaccine<br>|
|---|---|---|
||(1)|(2)|
|C300|0.193***|0.194***|
||(0.023)|(0.023)|
|C800|0.282***|0.281***|
||(0.026)|(0.027)|
|Observations|2482|2214|
|R-squared|0.094|0.118|
|Control mean of dependent variable|0.548|0.554|
|Covariates||X|
|Fixed effects by village (80 villages)|X|X|

_Source:_ Authors estimate _Notes:_ These are based on the analysis sample of 2,482 women. 268 observations with missing covariates are dropped in column (2). Robust standard errors clustered by village (80 villages) are in parentheses. Vaccine condition and Vaccine condition & Fear are controlled for. Covariates are Woman's age, Age squared, Muslim, Any education, Marital status = Single, Currently pregnant, Have children, Has paid work, Monthly HH earning per capita (naira), Distance to clinic (km), Transport to clinic (naira), Opportunity costs to clinic (naira), Ever used clinic, Received tetanus vaccine before, Likely to contract tetanus, Number of people who die of tetanus, Very worried about Tetanus, Tetanus is very bad, Very important to be protected from tetanus, Vaccine efficacy, Vaccines protect from disease, Needles are scary, Vaccines have side effects, Vaccines give diseases, Vaccines give HIV, Heart rate (beat/min). Control mean of dependent variable is the mean under C5 . * significant at 10%; ** significant at 5%; *** significant at 1%
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44
percentage of total energy saved by using each type of these measures is about 29% for floor insulation and 38% for both low-temperature and condensing boilers. The cost-effectiveness of energy renovation measures is widely dependent on energy prices. Through the exchange program of replacing inefficient bulbs with LED bulbs of 181 households in low-income areas of Salt Lake City, Utah, Witt et al. (2019) estimate that residents saved approximately US$18,219 annually in electricity bills, an equivalent of about US$100 per household. This translates to savings of about 2.6% of the total electricity consumed by each household. Using artificial neural networks and empirical models on a sample of 16 household refrigerator replacements under the Appliance Replacement Offer in low-income households in Australia, Ren et al. (2021) find most low-income households save, on average, 53% of their energy consumption in refrigeration through the replacement of old refrigerators with energy-efficient ones. However, they also find that some portion of the energy savings could be compromised if the size of a new refrigerator is larger than the old one.

It is not necessarily true that the adoption of clean or energy-efficient technologies reduces energy consumption. Employing a Logit regression model on 2010 household budget survey of Ireland, Chesser et al. (2019) show households that have adopted micro renewable energy systems, such as PV panels, micro wind turbines, solar thermal water heaters, wood pellet boilers, geothermal heat pumps and combined heat and power (CHP) units, have increased their electricity use. Using micro-level data from the National Survey of Family Income and Expenditure in Japan, Inoue and Matsumoto (2019) find households began spending more electricity on space cooling and food preservation after the implementation of the EE program that sets efficiency standards for major home appliances. They find that a large size and increased stock of home appliances contributed to an increase in the electricity use. Based on a controlled field experiment of 154 apartments in the Greater Boston area in 2011, Tiefenbeck et al. (2013) find residents who received weekly feedback on their water consumption (a proxy for environmental measures) lowered their water use by an average 6%, an equivalent of 0.5 kWh/person/day, but at the same time, they increased their electricity consumption by 5.6%, an equivalent of 0.89 kWh/person/day. They estimated that the energy saved by reduced (hot) water consumption is offset by the increased electricity consumption by nearly a factor of two. Jacobsen et al. (2012) also find that households in Memphis, Tennessee using the minimum threshold level (150 kWh per month) of green 31
# **Table 3: Changes in satisfaction with service delivery in transition countries, 2006-10**

||||**Percen**|**t of R**|**espond**|**ents S**|**atisfie**|**d With**|**Qual**|**ity and**|**Effic**|**iency**|**of Pub**|**lic Serv**|**ice D**|**eliver**|**y**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||**Pub**<br>|**lic He**<br>**System**|**alth**<br>||**Road**<br>**Police**|<br>|<br>**Do**|**Officia**<br>**cume**|**l**<br>**nts**|**Une**<br>**B**|**mploy**<br>**enefit**|**ment**<br>**s**|**Ot**<br> <br>|**her Soc**<br>**Security**<br>**Benefit**|**ial**<br> <br>**s**||**Civil**<br>**Courts**|<br>|
||**2006**|**2010**|**Ch.**|**2006**|**2010**|**Ch.**|**2006**|**2010**|**Ch.**|**2006**|**2010**|**Ch.**|**2006**|<br>**2010**|**Ch.**|**2006**|<br>**2010**|**Ch.**|
|Moldova|43|67|25|27|39|13|49|82|33|13|39|26|4|59|55|43|65|22|
|Russia|42|58|16|21|41|21|33|68|35|28|59|31|25|74|49|18|51|33|
|Turkey|51|79|28|41|39|-2|60|75|15|21|55|34|42|38|-5|35|49|13|
|<br>Tajikistan|37|57|20|21|36|15|34|62|28|11|38|27|26|42|15|38|29|-9|
|<br>Estonia|60|78|18|64|61|-4|73|90|17|49|70|21|63|73|10|48|76|28|
|Montenegro|49|60|11|28|51|23|54|71|17|20|28|8|22|53|31|22|42|20|
|<br>Romania|46|57|11|44|49|5|36|63|26|24|53|29|16|49|33|27|33|6|
|Belarus|49|59|9|43|50|7|42|73|30|17|66|50|29|60|31|49|54|5|
|Kazakhstan|39|54|15|24|40|16|36|50|14|42|43|1|38|50|13|35|27|-8|
|Bosnia-|50|55|5|30|56|25|54|75|22|33|15|-18|9|31|22|32|69|37|
|Herz|||||||||||||||||||
|Serbia|46|60|14|33|43|10|51|61|9|32|47|15|6|50|44|17|26|9|
|Ukraine|34|45|11|25|22|-3|42|57|15|11|41|30|20|57|37|28|34|5|
|Georgia|63|75|12|71|75|4|59|92|33|27|0|-27|21|28|7|43|36|-7|
|<br>Poland|46|62|16|50|52|2|67|81|14|32|39|8|41|49|8|51|57|6|
|Hungary|50|59|9|47|64|17|62|73|12|27|61|34|51|60|8|46|38|-9|
|<br>Slovenia|65|70|5|36|50|14|62|75|13|50|67|17|36|70|34|46|65|19|
|Czech Rep|60|66|6|27|45|17|51|70|18|35|47|11|42|43|1|28|44|16|
|<br>Croatia|65|70|6|55|64|9|54|72|17|29|54|25|30|69|39|41|35|-6|
|Latvia|56|70|14|50|53|3|65|80|14|76|74|-3|66|74|7|59|35|-24|
|Uzbekistan|48|64|16|41|43|2|48|54|6|14|14|-1|53|48|-5|25|29|4|
|Lithuania|56|64|8|49|56|7|56|72|16|53|78|25|60|67|7|53|44|-9|
|Albania|40|45|5|19|29|10|38|51|13|14|29|15|37|31|-6|29|47|18|
|Slovakia|58|64|7|43|49|6|56|70|15|12|37|24|37|42|5|39|45|6|
|Mongolia|48|53|4|19|14|-5|35|48|13|13|36|23|54|34|-20|18|17|-1|
|<br>Armenia|64|61|-2|32|44|13|62|70|8|27|39|12|50|43|-6|11|30|19|
|Kyrgyzstan|50|53|3|17|21|4|35|36|1|19|44|25|43|46|3|23|5|-18|
|<br>Bulgaria|60|61|1|23|26|2|72|52|-20|41|48|7|29|59|29|31|17|-15|
|<br>Macedonia|50|45|-5|38|41|3|53|44|-8|16|33|17|18|30|12|24|42|17|
|Azerbaijan|56|45|-10|24|16|-8|51|61|10|15|5|-10|21|12|-9|47|26|-21|

Notes: Ch. denotes change in satisfaction between 2006 and 2010. Countries sorted in order of average increase across all seven services. Data on satisfaction are not fully comparable between the 2006 and 2010 LiTS surveys. The 2006 survey asked respondents if ―you personally‖ used a service (and, conditional on use, whether you were satisfied); while the 2010 survey asked if ―you or anyone in your household‖ used the service.

16
# Box 1: Debt and Macro Data

In Figure 2, domestic debt is net of government deposits in the banking system and on-lending. External debt is on a gross basis and includes borrowings from the IMF.

In compiling statistics on external debt, data from 3 different sources were compared: World Economic Outlook and staff reports (IMF); Global Development Finance (World Bank); and the statistical bulletins of the Ministry of Finance (MoF) and the Central Bank (CBK). All institutions report data on gross external debt in dollars, by creditors or groups of creditors (See table). The difference reached as high as $1.2 billion in 2003/04.

||||<br>|External D<br>(In millions|ebt Compar<br> ofUS dolla|ison<br>rs)||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
||1996/97|1997/98|1998/99<br>|1999/00|2000/01|2001/02|2002/03|2003/04|2004/05|2005/06|2006/07|
|IMF|5,666|5,755|5,454|5,286|4,713|4,907|5,088|5,119|5,068|5,000|5,370|
|World Bank 1/|6,814|6,465|6,824|6,475|6,145|5,521|6,128|6,869|6,919|6,428|6,534|
|Kenya|5,915|5,366|5,476|5,426|4,988|4,795|5,488|5,573|5,695|5,837|5,955|
|Differencemax-min<br>Source: IMF WEO an<br>1/ Calendar year. It in|572<br>d Staff Repo<br>cludes use of|389<br>rts; GDF; an<br>IMF credit|22<br>d Statistica|253<br>l bulletins o|275<br>f the Minis|538<br>try of Finan|861<br>ce of Kenya|1197<br>|627|837|585|

Eventually, the choice fell on the data published by the MoF as better documented, consistent with monthly data published by CBK and consistent with past external borrowing requirements from the fiscal accounts.

Also, the collection of macro aggregates proved difficult. In 2005, the Central Bureau of Statistics updated the methodology for estimating GDP so as to better capture the contribution of services in the economy. The published series now goes back only to 1996, preventing a longer time series on the debt-to-GDP ratio. In addition, data on key macroeconomic variables such as the fiscal accounts, balance of payments, interest rates, prices and exchange rates are difficult to find from the same source on a consistent basis (i.e. IMF staff reports or GDF), for years before 1996.

Figure 2 Kenya: Public Debt (In percent of GDP) <!-- Start of picture text --> 80<br>Domestic debt<br>70 External debt<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07<br><!-- End of picture text --> 12
regular intervals from an alphabetic list), and to pursue face-to-face interviews, following up for clarifications where necessary. The employment distribution was taken from data in the 1998 _Yearbook of Labour Statistics_ of the International Labour Office. The respondents to the survey are typically a company’s CEO or a member of its senior management.” The WCY uses a 115 question survey sent to executives in top and middle management of firms in all 49 countries of the WCY. The sample size of each country is proportional to GDP, and firms "normally have an international dimension." The firms are selected to be a cross section of manufacturing, service, and primary industries. There were 3532 responses to the Survey. KKZ (2002) updates the data on governance that were developed in Kaufmann, Kraay and Zoido-Lobaton (1999) “Governance Matters.” The database contains more than 300 governance indicators for 175 countries compiled from a variety of sources in 2000/2001. Six aggregate indicators are constructed corresponding to six basic governance concepts: Voice and Accountability, Political Stability, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption.

The various raw data series were chosen because of their relevance to the four concepts of trade facilitation.

Port efficiency for each country _J_ is the average of two indexed inputs (all GCR): o Port facilities and inland waterways are :(1=underdeveloped, 7=as developed as the world's best, GCR) o Air transport is :(1=infrequent and inefficient, 7=as extensive and efficient as the world's best, GCR) Customs environment for each country _J_ is the average of two indexed inputs (all GCR): o Hidden import barriers other than published tariffs and quotas o Irregular extra payments or bribes connected with import and export permits Regulatory environment for each country _J_ is constructed as the average of four indexed inputs: o Transparency of government policy is satisfactory (WCY) o Control of Corruption (KKZ) Service sector infrastructure for each country _J_ is as the average of two indexed inputs (all GCR): o Speed and cost of internet access are: (1=slow and expensive, 7=fast and cheap) 19
# **Figure 1 (continued). Full-sample, correlations between infrastructure indicators vs per capita GDP, PPP (constant 2005 int'l $)**

# **(b)Telecommunications**

<!-- Start of picture text --> BDI ERIETHMOZCAFMWIRWATGOMMRMDGUGANPLMLIBFATZABGDHTIGINGHAZMBBENLSOKENSENSDNCIVMRTNGALAOKGZPNGCMRVNMMDAINDPAKYEMNICMNGPHLIDNCOGHNDGEOAGOLKAMARAZEARMBOLCHNPRYSYRGTMJORSWZNAM EGY DOMSLVALBUKRCOLBIHJAMPERTUNECUTHADZAMKDBLRKAZZAFBRACRIURYBGRPANROMIRNVENLBNMUSTURARGRUSMEXMYSCHLBWALVAHRVLTUPOLGABSVKESTHUNTTOCZEOMNPRTKORSAUISRSVNNZLESITAGRCFINJDEUFRAGBRSWEAUSBEL P DNKHKGAUTNLDCANNCHEIRLUSASGPKWTARENOR ZARLBRBDI GNBNERMOZCAFMWIRWATGOUGAMDGMLIBFATZABGDGMBHTIGINGHAZMBBENLSOKHMKENTJKTCDSENSDNCIVMRTNGALAOKGZUZBCMRVNMMDAINDPAKYEMNICMNGPHLIDNCOGHNDGEOAGOLKAMARAZEARMBOLCHNPRYSYRGTMJORSWZNAM EGY DOMSLVALBUKRCOLBIHJAMPERTUNECUTHADZAMKDBLRKAZZAFBRACRIURYBGRPANROMIRNVENLBNMUSTURARGRUSMEXMYSCHLBWALVALBYHRVLTUPOLGABSVKESTHUNTTOCZEOMNPRTKORSAUISRSVNNZLESPITAGRCFINJPNDEUFRAGBRSWEAUSBELDNKHKGAUTNLDCANCHEIRLUSASGPKWTARENOR<br>NER<br>TCD<br>ERI NPL<br>PNG<br>ETH<br>ZAR MMR<br>6 7 8 9 10 11 6 7 8 9 10 11<br>log of real per capita GDP log of real per capita GDP<br>MMR SDN HND<br>ERI<br>IND NPL<br>KENTJK<br>ZMB LSO<br>ETH UZB GHA<br>CIV<br>NER NPL<br>ERIMOZCAFMDG LSOTCD ARMSWZALB BDI GNBETHMWITGO GMBKEN YEM LKA SWZALBJAMDZA<br>AZENAMUKR KAZZAFMUS GAB MMRBGDBEN MNG<br>BFA JAM UKR<br>BDI RWATGOTZAGINGHABENSENSDNMRTNGAMDANICMNGPHLIDNHNDGEOLKMPRYSYR A JORR EGY SLVCOLBIHTUNECUTHADZAMKDBLRBRACRIPANBGRROMVENTURRUSMEXMYSCHLLVAHRVLTUPOLSVKESTHUNCZEOMNPRTKORSAUSVNTWNESPGRCJPNGBRAUSBELDNKHKGAUTIRLUSASGPKWTARE MOZCAFMDGBFATZAGINZMBTJKSENCIVLAOKGZPNGUZBMDAINDPAK GEOMARAZEARMBOLPRYJORNAM EGY SLVCOLPERTUNECUTHABLRKAZZAFBRCRIURYBGRPANROMIRNMUSTUR A RGRUSMYSBWACHLLVAHRVLTUPOLGABSVKESTHUNCZEOMNKORSAUSVNNZLTWNITGRFINJPNFRADEUGBRSWE A DNKHKGAUTNLDUS C ANHESGPKWTARENOR<br>6 7 8 9 10 11 6 7 8 9 10 11<br>log of real per capita GDP log of real per capita GDP<br>8 8<br>6<br>6<br>4<br>4<br>2<br>2<br>0<br>log of total mainlines (lines per 1,000 workers) log of cell phone lines (lines per 1,000 workers)<br>100 1<br>80 .8<br>60 .6<br>40 .4<br>.2<br>20<br>Telephone faults (per 100 main lines)<br>0<br>Waiting list (the ratio of waiting list to main lines)<br>0<br><!-- End of picture text --> 12
I

|Figure 6|Projected Population (billions) in Less Developed Countries,<br>1985-2025, Compared with U.N. and Previous World Bank Projections ......|xxiii|
|---|---|---|
|Figure 7|Projected Population (billions) in More Developed Countries;<br>1985-2025, Compared with U.N. and Previous World Bank Projections ......|xxiii|
|Figure 8|<br>Percentage Distribution of World Population by Continent, 1985 ....<br>..|....<br>xxiv|
|Figure 9|Percentage Distribution of World Population by Continent, 2000 ....<br>..|....<br>xxiv|
|Figure 10|Percentage Distribution of World Population by Continent, 2025 ....<br>.|..... xxdv|
|Figure 11|Population in Less Developed Countries by Age and Sex, 1985 ....|v......<br>Aii|
|Figure 12|Population in Less Developed Countries by Age and Sex, 2025 ....<br>...|...<br>xxvii|
|Figure 13|Population in More Developed Countries by Age and Sex, 1985 ....<br>...|...<br>xvii|
|Figure 14|Population in More Developed Countries by Age and Sex, 2025 ....<br>...|...<br>xvii|
|Figure 15|<br>Assumed Total Fertility Trend, Less Developed Countries, and U.N.<br>and Previous World Bank Trends ................................|xxx|
|Figure 16|Assumed Total Fertility Trend, More Developed Countries, and U.N.<br>and Previous World Bank Trends ................................|xxx|
|Figure 17|Assumed Life Expectancy Trend, Less Developed Countries, and U.N.<br>and Previous World Bank Trends .................................|xxx|
|Figure 18|Assumed Life Expectancy Trend, More Developed Countries, and U.N.<br>and Previous World Bank Trends .x.xx ...........||
|Figure 19|Percentage Contribution to World Population Growth from World Bank<br>Regions and Nonborrowers, 1985-2100 ...........................|xvii|
|Exhibit 1|Countries and Economies Classified by Income Group (based on GNP<br>per capita in 1987 U.S. dollars) ................................|xdii|
|Exhibit 2|Countries and Economies Classified by World Bank Region and Country<br>Department ..............................................|xxxiv|
# 4.2.2 Exploratory and Confirmatory Factor Analysis

A one-factor solution is chosen based on our criteria. All elements have salient factor loadings ≥ .4 (except for Social and Collaborative Skills). Figure 3 is a scree plot from this analysis that indicates the first dimension accounts for substantially more variation than subsequent dimensions. We conclude that a single dimension underlies item responses, which we assert based on content and cognition evidence as the quality of teaching practices. CFA also confirms this one-factor solution. The model has good statistical fit with χ<sup>2</sup> (35) = 145.91, CFI= .92, TLI=.90 and RMSEA=.06, verifying a single common factor explains the relationships among the element scores.

We also test a three-factor solution and find good fit statistics with χ<sup>2</sup> (df) = 98.51 (32), CFI= .95, TLI=.94 and RMSEA=.05. We interpret the likelihood ratio test, showing a three-factor solution has a better statistical fit than a one-factor solution, as evidence supporting the three underlying subdomains, largely due to our large sample size enabling detection of small differences. However, taken together, results in exploratory and confirmatory factor analysis suggest a one-factor solution is parsimonious and consistent with the intended use of the Teach score. Therefore, a one-factor solution is chosen. The resulting average score also demonstrates high internal consistency (Cronbach’s alpha (α) = .77).

**Figure 3** : _Teach_ Dimensionality

21