rafmacalaba/datause-encoder-data huggingface dataset:
in temperature. This means that floods of a certain size (or expected damages to the capital stock) will have shorter return periods as temperatures rise (Figure 9). These short return periods and higher probabilities of flooding can be translated to expected damages from increased inland flooding due to climate change (Figure 10).

**Figure 9: Flood return periods and damages for Uruguay under different warming scenarios**

<!-- Start of picture text --> 3000<br>2500<br>2000<br>1500<br>Historical<br>1000 RCP 2.6<br>RCP 4.5<br>500<br>RCP 8.5<br>0<br>0 200 400 600 800 1000 1200 1400 1600<br>Return period (years)<br>Source: UNDRR 2015 dataset and World Bank calculations.<br>Value of capital stock damaged (US$mil)<br><!-- End of picture text --> Source: UNDRR 2015 dataset and World Bank calculations. Note: 2023 US$ millions.

**Figure 10: Uruguay historical flood damages and expected flood damages under climate change**

<!-- Start of picture text --> Historical damages by flood return Annual expected damages (US$mil)<br>period 400<br>3.5% 3.5%<br>350<br>% of GDP<br>3.0% 3.0%<br>% of capital stock 300<br>2.5% 2.5%<br>250<br>2.0% 2.0%<br>200<br>1.5% 1.5%<br>150<br>1.0% 1.0%<br>100<br>0.5% 0.5%<br>50<br>0.0% 0.0%<br>1 20 50 100 250 500 1,000 1,500 0<br>Baseline RCP 2.6 RCP 4.5 RCP 8.5<br>Return period (years)<br>Source: UNDRR 2015 dataset and World Bank calculations.<br>Note: Based on economic values in 2023.<br><!-- End of picture text --> 16
## RESULTS

## Distribution of total costs bX i ctegor

Table 4 shows the distribution of recurrent and total district costs by broad input category. There are two striking features in this table. The first is the low proportion of recurrent costs absorbed by salaries and wages (27% to 39%). The second is the high proportion (46% to 57%) absorbed by the annual value of capital, of which buildings and equipment are the most significant and transport very small. As a proportion of total recurrent costs, drugs and medical stores take up between 24% and 37%, and vehicle-associated costs between 11% and 18%. Food, the only other significant item of recurrent expenditure, takes up 3% to 7%.

## Distribution of costs by cost centre

When costs are distributed by cost centre, the pharmacy is :the most costly department absorbing 2S% to 38% of total recurrent costs. Administration absorbs 5% to 9%, maintenance under 4% and in four districts under 2%, and the kitchen 5% to 9%. - The medical support departments apart from pharmacy laboratory, X-ray and theatre - have low direct costs.

# Distribution of recurrent costs by direct service departments and unit recurrent costs

Table 5 shows total recurrent costs distributed to 'irect service departments (wards, OPD, MCH, environmental health, and health centres and PHC), and.Tables 6 to 9 unit recurrent costs per bed, per inpatient, per inpatient day, per new outpatient and per 9
# THE EARMARKING OF GOVERNMENT REVENUES IN COLOMBIA

# Table of Contents

|I.|INT|RODUCTION........................................................1|
|---|---|---|
||A.<br>B.|Definition<br>of<br>Earmarking<br>......................................... 1<br>Types<br>of Earmarking<br>Found in Colombia............................ 2|
|II.|TRE|NDS IN THE SIZE AND STRUCTURE OF EARMARKING,1970-87<br>.<br>.<br>6|
||A.|Size and Structure of Earmarking ................................. 6|
||B.<br>C.|The Effects of Law 55 (1985)<br>..................................... 8<br>Consideration of Social Security and Public<br>Enterprise Profits ............................................<br>13|
|III.|THE|EXPERIENCE OF EARffARKING<br>**.17**|
||A.|The Origins of Earmarking .17|
||B.|Recommendations of Previous Government Commissions .19|
|IV.|AN|EVALUATION OF EARHARKING**.22**|
||A.|Revenue Sharing .22|
|||1. The Tax Allowance (Situado Fiscal) .23<br>2. Sales Tax Transfer (Cesion a las Ventas) .29|
||B.|National Government Level Earmarking .37|
|||1. Coffee Fund .37|
|||2. National Highways Fund (Gasoline Tax) .41|
|||3. PROEXPO .45|
||C.|Departmental Earmarking .48|
||D.|Municipal Level Earmarking .50|
||E.|Payroll Taxes.54|
|||1. Funds for Social Welfare Objectives .54|
|||2. Social Security .58|
|||<br>3. Employment Effects of Payroll Taxes .60|
|V.|SUM|HARY AND RECOMMENDATIONS ..............................<br>62|
|BIBLI<br>STATI|OGRA<br>STIC|PHY .69<br>AL APPENDIX|
|HP|0.414|3|HP|0.808|3|TamilNadu|1.649|3|
|---|---|---|---|---|---|---|---|---|
|Tamil Nadu|0.393|4|Tamil Nadu|0.746|4|Kerala|1.535|4|
|Karnataka|0.381|5|Gujarat|0.692|5|Gujarat|1.506|5|
|Haryana|0.351|6|Haryana|0.659|6|Karnataka|1.457|6|
|Gujrat|0.348|7|Karnataka|0.636|7|Haryana|1.294|7|
|Maharashtra|0.302|8|Maharashtra|0.605|8|Maharashtra|1.284|8|
|Andhra|0.270|9|WB|0.552|9|Chhattisgarh|1.132|9|
|Assam|0.255|10|Andhra|0.542|10|Rajasthan|1.062|10|
|Odisha|0.210|11|Chhattisgarh|0.479|11|WB|0.973|11|
|Rajasthan|0.208|12|Rajasthan|0.451|12|Assam|0.952|12|
|WB|0.202|13|Assam|0.416|13|Odisha|0.934|13|
|UP|0.172|14|MP|0.394|14|MP|0.920|14|
|MP|0.160|15|Odisha|0.381|15|UP|0.837|15|
|Chhattisgarh|0.125|16|UP|0.367|16|Bihar|0.696|16|
|Bihar|0.109|17|Bihar|0.301|17|Jharkhand|0.612|17|
|Jharkhand|0.097|18|Jharkhand|0.253|18|Andhra|0.462|18|
|CV|47.3|||39.5|||34.3||

Source: Author’s calculations. C.V- Coefficient of Variations

**_Social Infrastructure:_** Table 3 reports the score for the social infrastructure index and the relative ranking of the states. Like physical infrastructure, there is wide variation in social infrastructure across states, although the disparities have declined from 2010 to 2019. States such as Himachal Pradesh, Karnataka, and Assam are in the top ranks, whereas Uttar Pradesh, Jharkhand, and Bihar feature in the bottom positions. The relative positions of states have remained more or less constant, barring a few exceptions. For example, the relative position of Maharashtra has worsened (Rank 3 in 2005 to 11 in 2019), whereas Chhattisgarh and Assam have improved their respective ranks during the same period.

**Table 3: Relative Performances of States for Social Infrastructure Index**

||**20**|**05**||**2010**|||**2019**||
|---|---|---|---|---|---|---|---|---|
|**_States_**|**_Score_**|**_Rank_**|**_State_**|**_Score_**|**_Rank_**|**_State_**|**_Score_**|**_Rank_**|
|HP|1.652|1|HP|1.669|1|HP|1.868|1|
|Karnataka|1.071|2|Karnataka|1.313|2|Karnataka|1.400|2|
|Maharashtra|1.061|3|Kerala|0.984|3|Assam|1.379|3|
|Kerala|0.958|4|Chhattisgarh|0.908|4|Kerala|1.344|4|
|Tamil Nadu|0.899|5|Maharashtra|0.883|5|Tamil Nadu|1.281|5|
|MP|0.895|6|Rajasthan|0.876|6|Chhattisgarh|1.212|6|
|Rajasthan|0.888|7|Odisha|0.870|7|Rajasthan|1.158|7|
|Gujarat|0.808|8|MP|0.787|8|Punjab|1.154|8|
|Odisha|0.800|9|Assam|0.775|9|WB|0.977|9|
|Assam|0.788|10|Andhra|0.752|10|MP|0.963|10|
|Punjab|0.692|11|Punjab|0.727|11|Maharashtra|0.939|11|
|Chhattisgarh|0.679|12|Tamil Nadu|0.703|12|Odisha|0.903|12|
|WB|0.655|13|Gujarat|0.689|13|Gujarat|0.864|13|
|Andhra|0.612|14|WB|0.630|14|Haryana|0.806|14|
|Haryana|0.448|15|Jharkhand|0.460|15|Andhra|0.780|15|
|UP|0.354|16|UP|0.410|16|UP|0.752|16|
|Jharkhand|0.168|17|Haryana|0.396|17|Jharkhand|0.665|17|

17
# D. PUBLIC DEFICITS, EXTERNAL DEBT AND THE CURRENT ACCOUNT

Finally, we explore to what extent fiscal imbalances contributed to the persistent current account deficits of the nineties. The latter posed two risks: they increased vulnerability to capital flow reversals, and also added to the overvaluation of the currency - since, as we found above, much of the peso overvaluation can be traced to a steady deterioration of the net foreign asset position of the country.

What were the contributions of the private and public sectors to Argentina's external imbalance? Figure 4.9 depicts the overall fiscal balance of the consolidated government (exclusive of privatization revenues) and the private sector overall surplus - with the latter defined as the difference between the current account and the fiscal balance; thus, the sum of the private and public deficits equals the current account deficit by construction.

The figure reveals a contrast between the private and public sectors. While the public sector exhibited a deficit every year since 1993, the private sector alternated between deficit and surplus. In particular, after 1994 the private sector exhibited a current account deficit only in the boom years of 1997-98. By 1999 it had moved to a position of surplus, while the public sector continued to show large deficits. **Figure 4.9. Private and Public Current Account Balances (Percentage of GDP)** <!-- Start of picture text --> 4<br>2<br>0<br>-4 .<br>-.... Private Sector Balance<br>410-vera11 Public Sector Balance (excluding privatization revenues)<br>*8<br><!-- End of picture text -->

**Source: Ministerlo de Economla de la Rep(iblica** Argentina and World Bank.

40
- 14 -

expenses and taxes paid to government) may be considered earmarking because they are left to the control of the enterprises despite the fact that they are owned in whole or in part by the government; that is, the government cannot or in practice does not attempt to allocate such resources at irt discretion. Similarly, payroll taxes for social security imply an obligation to pay pensions and medical expenses now and in the future and the government has no discretion about how payroll tax receipts are to be used. Depending on the rates charged relative to the mortality and morbidity problems faced by the population, present revenues may be greater or less than the present payment obligations. That part of the payroll tax that is allocated to SENA and ICBF commits the public monies to funding a variety of activities in training, nutrition, daycare, and social welfare. In reality, therefore, such profits and payroll taxes are little different than the traditional cases of earmarking.

|Table<br>6Shares<br>of Trad<br>(incl. soc<br>|itional<br>ial secu<br>|and Non-<br>rityand<br>(perce<br>|Traditio<br>public<br>e<br>ntages)|nal Earm<br>nterpri|arkina i<br>sesprofits|n PublIc<br>)|Incom|ea||
|---|---|---|---|---|---|---|---|---|---|
|1970|1975|1980|1981|1982|1983|1984|1985|1986|1987|
|Share<br>in national<br>public<br>income<br>28.6|31.8|39.3|38.2|43.3|43.0|54.2|49.9|44.9|46.0|
|Share<br>in departmental<br>public<br>income||90.9|88.5|89.3|88.4|82.0|80.8|||
|Share<br>in municipal<br>public<br>income||61.4|65 0|65.9|67.9|63.4|67.2|||
|Share<br>in Public<br>Income<br>All levels||45.5|44.6|48.7|49.1|57.8|54.6|||

a. Public income is the sum of tax and non-tax revenues, operating profits of public non-financial enterprises, and payroll taxes for social security and for SENA, ICBF, etc. The ad valorem coffee export tax is added to national public income 1970-83 since these revenues did not pass through the budget in those years. The earmarking considered here is traditional earmarking plus non-traditional earmarking which includes non-financial public enterprise profits and payroll taxes for social security **and** SENA, ICJF, etc.

Source: **Estimates** based on Tables **Al and** A2 in Statistical Appendix.
# **1. Introduction**

A well-known challenge in studies on the influence of peers in children’s outcomes is that of identification of social effects. According to Manski (1993), peer effect can be explained by two distinct hypotheses. The hypothesis of “endogenous social effect” states that individual behavior is motivated by the average behavior of others in a reference group. Second is the hypothesis of “contextual effect”: an individual’s behavior in the group varies with the exogenous characteristics of the reference population. In addition to the conventional problem of omitted variable related bias, identification of an endogenous social effect is complicated by the “reflection problem”: mean behavior of peers is also affected by the individual’s own behavior.

Although there exists is a sizable empirical literature on social interactions in school participation and attainment decisions, research exploring peer effects on student achievement, particularly using developing country data, is limited<sup>1</sup> . Extant studies employ a variety of techniques to resolve the identification problems such as experimental design (e.g. Bobonis and Finan, 2007), school fixed-effects (Arcidiacono and Nicholson, 2005; Ammermueller and Pischke, 2006) and instrumental variable approach. Two recent studies have attempted to resolve the issue of identification within an instrumental variable framework. Cipollone and Rosolia (2007) use data on earthquake shocks in Italy and the subsequent relief from military training of males to identify social effects on school completion of Italian females<sup>2</sup> . On the other hand, Lalive and Cattaneo (2006) identify the peer effect on school attendance decision for a sample of children in Mexico who were ineligible for a randomly targeted school grant program. Identification is established using variation in mean schooling of peers due to exposure to the school grant by a fraction of the peers. In both studies, existence of an exogenous shock affecting the schooling outcome of a sub-sample of peers has been central for the purpose of identification. We note that in rural Bangladesh, a significant part of the population has been exposed to arsenicosis -- intake of arsenic-contaminated drinking water at home – which has serious health and learning implications<sup>3</sup> . Continuous drinking from arsenic-laced wells is highly cancerous and causes

> 1 See Soetevent (2006) for an extensive review.

> 2 Boys high school graduation rate is instrumented with the exemption from compulsory military service.

> 3 The extent of the crisis is nation-- according to Rohde (2005), as many as 20 million Bangladeshis have been drinking groundwater water contaminated with naturally occurring inorganic Arsenic for nearly over two decades (see Geen, Ahmed and Madajewicz (2005) for a detailed account of the crisis).

2
Schutte, N. S., Malouff, J. M., Hall, L. E., Haggerty, D. J., Cooper, J. T., Golden, C. J., and Dornheim, L. (1998). Development and validation of a measure of emotional intelligence. _Personality and individual differences_ , 25(2):167–177.

Schwarzer, R. and Jerusalem, M. (1995). Generalized self-efficacy scale. _Measures in health psychology: A user’s portfolio. Causal and control beliefs_ , pages 35–37.

Selman, R. L., Beardslee, W., Schultz, L. H., Krupa, M., and Podorefsky, D. (1986). Assessing adolescent interpersonal negotiation strategies: Toward the integration of structural and functional models. _Developmental Psychology_ , 22(4):450.

Seron, C., Silbey, S. S., Cech, E., and Rubineau, B. (2016). Persistence is cultural: Professional socialization and the reproduction of sex segregation. _Work and Occupations_ , 43(2):178–214.

Soto, C. J., Napolitano, C. M., and Roberts, B. W. (2021). Taking skills seriously: Toward an integrative model and agenda for social, emotional, and behavioral skills. _Current Directions in Psychological Science_ , 30(1):26–33.

Valerio, A., Sanchez Puerta, M. L., Tognatta, N., and Monroy-Taborda, S. (2016). Are there skills payoffs in low-and middle-income countries? empirical evidence using step data. _World Bank Policy Research Working Paper_ , (7879).

Von Stumm, S., Chamorro-Premuzic, T., and Furnham, A. (2009). Decomposing selfestimates of intelligence: Structure and sex differences across 12 nations. _British Journal of Psychology_ , 100(2):429–442.

Wang, M.-T. and Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. _Educational Psychology Review_ , 29:119–140.

27
# **5.4.1 Data**

I briefly discuss time-series data used to form nowcasts of Brazilian quarterly real GDP growth. All categories of economic data typically included in a GDP-nowcasting model are used here and divided into eight blocks: labor, trade, industrial production, survey, GDP and income, monetary and credit, financial and interest rate, and government finance.<sup>8</sup> All series are monthly data from January 2004 to December 2013. There are capital controls in most of the years in the sample period except 2004 and 2005. These two years are included to have a long enough sample period to train the forecasting model.

# **5.4.2 Empirical methodology**

I adopt the econometric framework in Giannone, Reichlin and Small(2008), widely used by central banks in advanced economies, to produce real-time nowcasts of quarterly Brazilian real GDP growth in a ten-year period between 2004 and 2013. Capital control measures are then added to my information set and they are shown to improve the precision of my nowcasts. I briefly describe the econometric framework below and refer interested readers to the original paper for more detail.

Let Ω _vj_ be the available information set of data vintage _vj_ following release j in month v. The information set consists of: where _xit|vj_ is a generic data series in the information set Ω _vj_ used to form the nowcast, _i_ = 1 _, ..., n_ indexes individual time series (exports, unemployment, etc...), _t_ = 1 _, ..., Tvj_ indexes dates a series in vintage _vj_ is observed ( _Tvj_ the period in which series i in vintage _vj_ is last observed). Assuming no data revisions, the information set is expanding with each release. Let _k_ = 1 _,_ 2 _,_ 3 _, ..._ index quarters, and hence 3 _k_ represents the third month of a quarter (3 _k −_ 1 the second month of a quarter and 3 _k −_ 2 the first month). Let _y_ 3 _k_ be quarterly GDP at the end of the third month of a quarter

> 8Table 8 in the appendix provides details of the data series. Each series is typically released at the same point in time in a given month. Table 8, as a calendar of data release, also gives the order in which data enters into the nowcast model.

32
matched only by a much smaller reduction in demand, with the consequence of a overall increase in the international price of poultry during the worst period of avian influenza outbreaks.

Figure 1 – Prices of Unprepared Poultry (Current USD per kg.) <!-- Start of picture text --> 1995 2000 2005<br>Year<br>HPAI free areas HPAI affected areas<br>2.5<br>2<br>1.5<br>USD per kg<br>1<br>.5<br><!-- End of picture text --> A related concern to the international trade of unprepared poultry meat is the possibility that HPAI infected countries have diverted part of their export to third countries with no or less restrictive import bans. The data generally does not support this hypothesis. Exports from Thailand to Africa, for example, have been following a similar pattern of those to other countries, with most exports halting by early 2004.<sup>19</sup>

> 19 However, it is still possible that some “dumping” of poultry product has occurred illegally through misclassification at customs. This hypothesis can not be verified by the analysis of the official data and would require further investigations.

16
_COTE D’IVOIRE: Competitiveness, Cocoa, and Real Exchange Rates_

# **7. Concluding Remarks**

**We have generated a twelve-partner index of the multilateral REER with dynamic weights that shift over time as trade partner patterns shift; the results indicate that Cote d’Ivoire’s competitiveness declined from 1996 to 2002, establishing a downward trend.** The index appears to characterize the country’s non-competitiveness prior to 1994 and the impact of the devaluation. The set of indices based on the GDP deflator seems better than those based on CPIs on theoretical grounds, and shows the afore-mentioned competitiveness pattern rather clearly. The multilateral REER indices cover most of Cote d’Ivoire’s trade, always 60%, usually more than 70%, and as much as 85% in early years. The bilateral REER with France moves somewhat differently from the multilateral REER against twelve major trade partners. Given the dramatic shift in the distribution of trade over the period, it seems clear that a multilateral REER index using fixed weights calculated on a single base year would not be adequate, as it would be very unrepresentative for most years.

**Cote d’Ivoire’s universe of trade partners has expanded over the last four decades.** The commonly held perception that links with France dominate Cote d’Ivoire’s trade are no longer true, although the link with France remains an important trade link. The country has diversified sources of imports, and the customer base for exports. The country has moved from relying upon a single trade partner, to trade with much of the world.

**Cote d’Ivoire has not, however, diversified its mix of export products and this seems to be a source of its continued external vulnerability.** It relies heavily upon cocoa bean exports, and also to a lesser extent upon coffee beans and cotton, that is, volatile agricultural commodities. All these three have volatile international prices which have declined steadily in real terms ever since 1976.

**We tested the hypothesis that world cocoa prices impact the competitiveness of Cote d’Ivoire via it’s real exchange rate and found evidence of “Dutch Disease”, i.e., that upturns in the real price of cocoa cause a change in the real exchange rate and make the country less competitive.** Even though it has a nominal fixed exchange rate regime, the Cote d’Ivoire CFA franc’s strong link to the key commodity price indicate its characteristics of a “commodity currency” or, more specifically, a cocoa currency, heavily impacted by world commodity prices. We also found evidence that the devaluation of 1994 improved the country’s competitive position, shifting the schedule of the real exchange rate with respect to cocoa prices.

**We also complemented the analysis by a very preliminary look at recent data on wages, employment, and value added by sector, looking for indications of trends in competitiveness.** This indicates that slow growth is continuing, slower than that of inflation combined with labor force growth while wages grew very slightly less than value added.

16
# **Table V**

## **Arm's Length Royalty Payments and IPR Regime Changes**

The dependent variable in each specification is the log of one plus the value of royalty payments made by unaffiliated foreign persons to US firms for the sale or use of intangible assets. The Post Reform Dummy is a dummy equal to one in the year of and the years following the reforms identified in Table II. The Difference of Host Country Tax Rate and US Tax Rate is the difference between the corporate income tax rate in the host country and the US corporate income tax rate. The Host Country Tax Rate and the Host Country Withholding Tax Rate are annual median tax rates paid by affiliates in a host country. Host Country Inward FDI Restrictions is a dummy equal to one when inward FDI restrictions exist, and it is drawn from Brune (2001). Host Country Trade Openness is the index of constant price openness taken from Heston, Summers, and Aten (2002). The Log of Host Country GDP per capita is derived from data provided in the World Bank World Development Indicators (2003). All specifications include firm/country fixed effects as well as country specific time trends. Heteroskedasticity-consistent standard errors appear in parentheses.

|Dependent Variable:||||
|---|---|---|---|
||(1)|(2)|(3)|
|Constant|13.7093|97.0149|11.8042|
||(25.7812)|(99.3360)|(31.4634)|
|Post Reform Dummy|0.0454|0.0904|0.0592|
||(0.0261)|(0.1028)|(0.0292)|
|Difference of Host Country Tax Rate and US Tax Rate|-0.0389|-0.6281|0.1346|
||(0.1670)|(0.6535)|(0.1978)|
|Host Country Withholding Tax Rate|-1.0048|-1.9413|-0.7489|
||(0.5452)|(1.9997)|(0.6592)|
|Host Country Inward FDI Restrictions|-0.1451|-0.1782|-0.1405|
||(0.0758)|(0.2386)|(0.0911)|
|Host Country Trade Openness|-0.0004|0.0056|-0.0019|
||(0.0028)|(0.0134)|(0.0034)|
|Log of Host Country GDP per Capita|0.4540|0.5724|0.5373|
||(0.2009)|(0.6856)|(0.2385)|
|Parent/Country and Year Fixed Effects?|Y|Y|Y|
|Country Specific Time Trend?|Y|Y|Y|
|No. of Obs.|46,460|4,871|28,914|
|R-Squared|0.7643|0.7642|0.7481|

48