rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 6. Cumulative spending multiplier +/- 90 confidence intervals. Using spending forecast errors. Typical economic expansions versus recessions, and increases (** ∆G>0 **) versus decreases (** ∆G<0 **) in spending. OECD countries.**

Panel A. Expansions & ∆G<0 Panel B. Expansions & ∆G>0 <!-- Start of picture text --> 4 4<br>3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>-3 -3<br>0 1 2 3 4 0 1 2 3 4<br>Semester Semester<br>Panel C. Recessions & ∆G<0 Panel D. Recessions & ∆G>0<br>4 4<br>3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>-3 -3<br>0 1 2 3 4 0 1 2 3 4<br>Semester Semester<br>Cumulative multiplier Cumulative multiplier<br>Cumulative multiplier Cumulative multiplier<br><!-- End of picture text -->
- 34 -

differentials occurring for air transport, is observed for most of the countries listed in Table 7. 23/

# IV. Summary and Conclusions

The major purpose of this study was to assess the validity of allegations that unfavorable international transport differentials have a general unfavorable influence on Caribbean exporters. The analysis is based on very detailed freight cost information for the United States which constitutes the destination for approximately 60 per cent of Caribbean countries' exports. Overall, the empirical analaysis shows no evidence of adverse freight rates for the Caribbean as opposed to all other exporters to the United States. However, some particular products (or sectors) like foodstuffs appear to sometimes have high relative transport costs and these might be "flagged" for more detailed analysis.

Perhaps a key finding is that a distinction must be made between Caribbean freight rates for air cargo as opposed to ocean transport. For the former, exports from almost all Caribbean countries included in this analysis generally encounter significantly lower average freight rates than their competitors. How to best exploit this advantage should be an important consideration in planning new export ventures, or in considering ways that the competitive position of established exports might be improved. The importance of these favorable transport costs for Caribbean countries is underscored by the fact that over one-third of all shipments to the United States (excluding

- 23/ Approximately one-half of the large (over 5.1 points) favorable ocean freight rate differential for the Bahamas occurs for food products: fresh fish; cucumbers; peppers; grapefruit; lemons; limes; carbonated drinks; etc. See the appendix for details. It may be that Bahamas proximity to the U.S. is the main reason why its overall distribution of air and ocean freight rate differences does not follow the pattern for other Caribbean countries.
- 32 -

- (1) KD deposits in foreign banks were no longer considered liquid assets from April 1979. This led to an active Kuwaiti interbank market and reduced the proportion of foreign assets to total assets from 33 percent in 1979 to 24.6 percent in 1982.

- (2) To reduce the banklng system's exposure to overdrafts, the ratio of overdrafts to total credit facilities was reduced from 55 percent to 40 percent between 1980 and 1982. As banks changed their lending structure to a larger proportion of loans, clients drew their money immediately since they were being charged interest, and invested in the stock market. Under the overdraft system clients were only charged interest when they withdrew funds.

- (3) Instead of lending at low interest rates to productive sectors, the banks found it more profitable to make term loans to individuals and financial institutlons. These loans returned higher rates and yielded more income through compensatory financing, commissions, and fees.

It seems clear that the CBK's policies were too weak, and in fact a number of indicators should have served as warning signals, includlng: the rapid increase in lending to nonproductive sectors; the high concentration of loans to large borrowers in the portfolios of commereial banks 41/ ; and the inflation in stock and real estate prices whieh the commercial banks accepted as security. (see figure 8).

41/ See Statistical Appendix 7.
Table 3 Impact of Investigations on Import Prices: Industry Means

|SITC|<br>Description|Inve|stigati|on|Contr|ol Group||
|---|---|---|---|---|---|---|---|
|||Pre|Post|<br>Dif|Pre|Post|Dif|
|2482|Softwood Lumber 1/|96.6|107.1|10.5|98.2|96.7|-1.5|
|6359|Wood Products|104.7|103.6|-1.1|105.3|102.6|-2.7|
|6822|Copper/Alloys, Worked|91.8|90.3|-1.6|102.8|103.0|<br>0.2|
|6991|Locksmith's wares<br>of base metal|98.0|101.0|<br>3.1|103.8|113.2|<br>9.4|
|7452|Packaging, weighing<br>non-elec machinery|91.4|85.7|-5.7|97.4|93.5|-3.9|
|7491|<br>Roller bearings|96.4|93.4|-3.0|95.2|93.2|-2.0|
|7492|Appliances for<br>liquid flow control|97.4|98.2|<br>0.8|95.9|92.4|-3.5|
|7781|Batteries|97.0|91.6|-5.4|100.0|93.0|<br>-7.0|
|7788|Misc elec machinery|96.3|92.6|-3.8|97.8|94.1|-3.7|
|8421|Woven coats, men's|100.3|101.6|<br>1.3|92.9|87.0|-5.9|
|8423|Woven pants, men's|100.5|98.4|<br>-2.2|92.9|87.0|-4.0|
|8441|Woven shirts, men's|102.7|114.1|11.4|92.9|87.0|-4.0|
|8451|Knitted sweaters|98.2|105.0|<br>6.8|92.9|87.0|-4.0|
|8482|Plastic/Rubber<br>apparel|99.1|97.7|-1.3|94.5|86.3|-8.2|
|8942|Toys and games|100.2|100.6|<br>0.4|96.8|91.6|-5.2|
|8947|Sporting goods|98.9|97.3|-1.6|96.8|91.6|-5.2|
|Sample|Mean|97.6|98.6|<br>1.0|97.3|93.7|-3.6|
|T-Test|of Difference in Means|Differ<br>T-valu|ence<br>c|4.1<br>2.7||||

1/ Since no other products available in SITC 2, all products used as control.

21
# TABLE VIII

IMPACTS OF PRICE INCREASE IN BILL 0 ON CONSUMPTION IN PERIOD 1, ALTERNATIVE FUNCTIONAL FORMS

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|Treatment|-15.901**|-15.266**|-15.577**|-15.597*|-16.539*|-14.595|-16.516*|-17.126|
||(6.491)|(5.929)|(6.153)|(9.194)|(9.201)|(9.917)|(9.174)|(12.408)|
|AAC|0.720**|1.004**|0.707**|2.201|0.812|7.515**|0.811|2.352|
||(0.290)|(0.412)|(0.272)|(1.441)|(0.702)|(2.872)|(0.696)|(5.143)|
|AAC* Ttt||-0.619||-2.777||-12.721***||-2.244|
|reamen||(0.531)||(1.968)||(3.936)||(8.023)|
|AAC<sup>2</sup>|||-0.011|0.059|-0.011|0.738**|-0.012|-0.487|
||||(0.012)|(0.069)|(0.012)|(0.356)|(0.044)|(1.014)|
|AAC<sup>2</sup>*Treatment||||-0.014||-0.149||-0.009|
|||||(0.090)||(0.465)||(1.619)|
|AAC<sup>3</sup>|||||-0.000|0.023*|-0.000|-0.074|
||||||(0.002)|(0.012)|(0.001)|(0.079)|
|AAC<sup>3</sup>*Treatment||||||-0.040**<br>(0.015)||0.136<br>(0.121)|
|AAC<sup>4</sup>|||||||0.000|-0.002|
||||||||(0.000)|(0.002)|
|AAC<sup>4</sup>*Treatment||||||||0.001<br>(0.003)|
||433.271***|436.134***|434.620***|439.962***|435.079***|447.792***|435.135***|443.718***|
|Constant|(3.299)|(3.992)|(3.539)|(6.161)|(4.700)|(6.506)|(5.037)|(8.874)|
|N|7190|7190|7190|7190|7190|7190|7190|7190|
|R-squared|0.001|0.001|0.001|0.001|0.001|0.002|0.001|0.002|

_Notes:_ The dependent variable is consumption in Period 1. Average of the dependent variable is 425.49. The estimation method is OLS. Standard errors clustered by accumulated consumption in Period 0.*** p<0.01, ** p<0.05, * p<0.1.

33
the currency, and those with less flexible exchange rate regime (e.g. those below the median) have an insignificant correlation between the cyclicality of capital flows and that of the currency.<sup>14</sup>

**Figure 6: Currency Cyclicality Index and Exchange Rate Regime**

<!-- Start of picture text --> CCI = -0.14 + 0.10*Exchange Rate Regime<br>(1.47) (2.80)<br>KOR IDN<br>URY<br>UKR TUR<br>THAMYS PHL NZLMEXARGISL<br>SWE ROM<br>GRCESPFINPRTINDSVK CZE IRNHUNCOLCHL RUSPOLAUSPER BRA<br>GBR<br>DNKITAMARCHNSVNCANHRV MLT NORISR GEO ZAF<br>BLZAUTFRACYP CRI MKD BOL DEU USAJPN<br>HKG BGR LVA<br>NLD LTU<br>IRL CHE<br>EST<br>1 2 3 4 5<br>Exchange Rate Regime<br>1<br>.5<br>CCI<br>0<br>-.5<br><!-- End of picture text --> Note: Exchange rate regime takes values from 1 to 6, 1 indicating “strongly fixed” and 6 “strongly flexible” exchange rates. The t- statistics are reported in parentheses.

The implications that follow are that countries can influence the degree of cyclicality of their currency by choosing their exchange rate regime, as well as the degree of openness of their capital account. This is corroborated in Figure 7, which shows that the countries with more procyclical currencies seem more inclined to impose controls on the capital account (we use the Chinn and Ito’s index of capital account openness).<sup>15</sup> Using a common parlance, these results indicate that the countries with procyclical currencies tend to “lean against the wind” by maintaining controls on their capital account.

> 14 Results are available upon request.

> 15 The Chinn and Ito index is based on binary dummy variables that codify the tabulation of restrictions on cross-border financial transactions reported in the IMF’s _Annual Report on Exchange Arrangements and Exchange Restrictions._ The last update of the index (2011) gives a score of 2.44 to the “most financially open” country, and a score of -1.86 to the “least financial open” country.  The annual data for this index goes from 1975 to 2011 and is obtained from <u>http://web.pdx.edu/~ito/Chinn-Ito_website.htm.</u>

11
this would suggest that the collective choice channel accounts for the results. If income and inequality mattered in untreated but not in treated municipalities, this would suggest that the political power channel accounts for the results. If they had significant but distinct effects in treated versus untreated municipalities, this would suggest a role for each channel.

Such a policy experiment is not feasible. However, following Brazil’s return to democracy in 1985, many municipalities put in place an institution that did something similar: Participatory Budgeting (PB). Under PB, citizens vote on how to use a share of municipal revenue designated for their neighborhood, and elect neighborhood representatives to make municipality-wide spending decisions. Citizens deliberate and negotiate over the distribution of public resources. Policymakers are required to publicize budgets and expenditures to promote transparency (Boulding and Wampler 2010). Case studies from Brazil suggest that PB increases participation of marginalized groups, leads to more pro-poor expenditures, and increases government accountability (Souza 2001). By dividing the budget into shares, PB mechanically ensures a quite equal distribution of power (unless the rich somehow live in all neighbors, and dominate policymaking).

According to Melo (2009), “One of the most salient aspects of PB is that most experiences originated in municipalities where an elected mayor lacked the support of the local legislative chamber (municipal council).” The legislature can veto any budget, but finds it politically difficult to do so when the budget comes from the people, through PB. When divided government paralyzes policymaking, mayors implement PB to get the policy process moving again. More often then not, PB has remained in place following its implementation.

I use data on which municipalities had PB at some point during the sample period. The data are available for all municipalities with a population over 50,000—about 14% of the sample. I estimate the baseline model for three sets of municipalities: large municipalities (population over 50,000), large municipalities with PB, and large municipalities without PB.

Table 11 shows how the effects of income and inequality on spending vary by the presence of PB. I use three dependent variables: the public pre-primary enrollment rate, education spending per capita, and the teacher quality index. I measure income with the per capita median. Inequality does not seem to moderate the effect of revenue on public pre-primary quantity or 27
<mark>Schweitzer, Mark E., and Scott Shane (2016). “The Ins and Outs of Self-Employment: An Estimate of Business Cycle and Trend Effects,”</mark> _<mark>Federal Reserve Bank of Cleveland Working Paper</mark>_ <mark>, no. 16-21.</mark> Shiferaw, Admasu, (2009) “Survival of private sector manufacturing establishments in Africa: The role of productivity and ownership”, _World Development_ 37(3), 572–584.

Singh, Inderjit J., Lyn Squire, and John Strauss (1986) _Agricultural Household Models: Extensions, Applications and Policy._ John Hopkins University Press, Baltimore.

Söderbom, Måns, Francis Teal, and Alan Harding (2006) “The Determinants of Survival Among African Manufacturing Firms”, _Economic Development and Cultural Change_ 54(3): 533-55.

Strauss, John, Firman Witoelar, and Bondan Sikoki (2016) “The Fifth Wave of the Indonesia Family Life Survey (IFLS5): Overview and Field Report”, WR-1143/1-NIA/NICHD.

Townsend, Robert M. (2016) “Townsend Thai Project Household Annual Resurvey, 2014 (Urban)”, doi:10.7910/DVN/UOOUAZ, Harvard Dataverse, V1.

Van Biesebroeck, Johannes (2005) “Firm Size Matters: Growth and Productivity Growth in African Manufacturing”, _Economic Development and Cultural Change_ 53(3): 545-83.

Vijverberg, Wim and Jonathan Haughton (2004) “Household Enterprises in Vietnam: Survival, Growth, and Living Standards”, pp. 95-132 in David Dollar and Paul Glewwe (eds.) _Economic Growth, Poverty, and Household Welfare: Policy Lessons from Vietnam_ . The World Bank, Washington D.C.

28
HK choose the elasticity of substitution =3 and capital rental rate R=10%, assuming a real interest rate of 5% and a depreciation rate of 5%.<sup>6</sup> Capital share, , and labor share ( ) are taken σσ from the U.S. manufacturing sectors. The authors assume U.S. firms operate in an environment of ss ss minimal distortions. Thus, the U.S. shares represent an efficient utilization of resources, and any αα 1 −αα deviation would suggest distortions.

> 6 Elasticity of substitution between products is related to the mark-ups −1 , where is the markup. An elasticity of σσss substitution of 3 corresponds to a markup of 50%. σσss = 1 + μμss μμss

7
31 impact of policies on income<sup>distribution.</sup> It includes a broad menu of approaches with a considerable<sup>range of detail. The complexity of the issue is</sup> such that one integrated model capable<sup>of answering all questions is infeasible.</sup> Instead, there is a menu of methodologies<sup>and the specific issues facing the</sup> country, as well as the data<sup>and resource availabilities, will determine the</sup> practical approach.

In a data-poor country without<sup>microsurveys or good macrodata, a more</sup> qualitative, partial equilibrium<sup>analysis will be required. An example of such</sup> a methodology is the IMF (1988)<sup>study which identifies poverty groups and</sup> discusses likely impacts of macropolicies<sup>in terms of the sources and uses of</sup> income for these poor groups.<sup>Additionally, an analysis of the operation of the</sup> labor market would help to understand<sup>how different groups are affected by income</sup> generating mechanisms.

If the country has a microsurvey,<sup>then poverty profiles can be quantitative</sup> and more detailed (see Glewwe<sup>and de Tray (1988,1989), Kanbur (1988), Kakwani</sup> (1990) and Ravallion and Huppi<sup>(1989)). Changes in poverty can be calculated</sup> by estimatir.g the elasticity<sup>of a poverty index to changes in income and changes</sup> in relative prices, and applying<sup>these elasticities to regional growth rates and</sup> price changes.

In a data-rich country, macro<sup>and microdata can be combined to construct</sup> a computable general equilibrium<sup>model to generate quantitative estimates of the</sup> impact of adjustment policies.<sup>In these models, particular attention must be</sup> paid to macro closure rules. They can have significant effects<sup>on the</sup> distributional outcomes and<sup>so they need to be selected to accurately reflect</sup> the particular country situation.<sup>In addition, sensitivity analyses should be</sup> carried out for certain key<sup>parameters that are difficult to estimate from the</sup>
Table 7: Innovation Capacity and Post-Sanction Innovation Performance

||(1)<br>**Pat**<br>Total|(2)<br>**ent Applic**<br>Intl.|(3)<br>**ation**<br>High-Tech|
|---|---|---|---|
|Treatment_×_Post|-0.163***|-0.223***|-0.058|
||(0.040)|(0.039)|(0.267)|
|Treatment_×_Post_×_Top|0.156***|0.140*|0.060|
||(0.037)|(0.078)|(0.046)|
|No. Obs|6,334|6,334|6,334|
|R-squared|0.63|0.611|0.645|
|Firm FE|Yes|Yes|Yes|
|Sector-year FE|Yes|Yes|Yes|

Note: We estimate the coefficients using OLS. Robust standard errors clustered at the 2-digit ISIC sector level are in parentheses. ***, **, and * indicate significance at levels 1 percent, 5 percent, and 10 percent, respectively.

Table 8: Knowledge Distance and Post-Sanction Innovation Performance

||(1)<br>**P**|(2)<br>**atent Ap**|(3)<br>**plication**|(4)|
|---|---|---|---|---|
|Treatment_×_Post|-0.666***|-1.416**|-3.199**|-8.297*|
||(0.195)|(0.511)|(1.417)|(4.290)|
|Treatment_×_Post_×_TechDist|0.033***<br>(0.009)||||
|Treatment_×_Post_×_Sourcing||0.023**<br>(0.008)|||
|Treatment_×_Post_×_Adoption|||0.039**<br>(0.017)||
|Treatment_×_Post_×_Collaboration||||0.087*<br>(0.045)|
|No. Observation|6,334|6,334|6,334|6,334|
|R-Squared|0.631|0.631|0.631|0.630|
|Firm FE|Yes|Yes|Yes|Yes|
|Sector-year FE|Yes|Yes|Yes|Yes|

Note: We estimate the coefficients using OLS.Robust standard errors clustered at the 2-digit ISIC sector level are in parentheses. ***, **, and * indicate significance at levels 1 percent, 5 percent, and 10 percent, respectively.

40
women, even if early initiation of care matters a great deal for high‐risk patients. High risk patients include, among others, smokers, substance abusers, those with poor medical and pregnancy histories, and those who start prenatal care very late in their third trimester or only when a problem occurs. It may be that the increase in early initiation of care comes from primarily low‐risk mothers who are less likely to benefit from early initiation of care. One would think that it would be easier to persuade low‐risk mothers to come a littler earlier than to convince high‐risk mothers who are reluctant to come for any care at all.

In fact, this is consistent with the small reduction in the average weeks pregnant at the time of the first prenatal visit. On average, women in the treatment group initiated prenatal care about 1.5 weeks earlier than women in the control group. Prenatal care may affect birth outcomes by diagnosing and treating illness such as hypertension and gestational diabetes as well as trying to change maternal behavior through promoting activities such as good nutrition, not smoking and not consuming alcohol. If the intervention had induced high‐risk women who otherwise would have had 1st visit much later in the pregnancy, then the incentives may have had a measurable impact on birth outcomes. Hence, while the incentives were effective in increasing early initiation of care, they did not manage to sufficiently affect the group most likely to benefit. The solution might be to condition incentives on attending high‐risk women, but risk is difficult and expensive to identify and verify and therefore may not be contractible.

# **9 DISCUSSION**

We examine the effects of temporary financial incentives for medical care providers to increase early initiation of prenatal care for pregnant women using a randomized controlled trial in Argentina. The intervention randomly allocates a three‐fold increase in the fee paid to health facilities for each initial prenatal visit that occurs before week 13 of pregnancy. This premium was implemented for a period of 8 months and then ended. Using data on health services and birth outcomes from medical records, we investigate both the short‐term effects of the incentive and whether the effects persist once the direct monetary compensation disappears.

Our results suggest that the temporary incentives motivated long‐run changes in performance. We find that the incentives led to pregnant women being 35% more likely to initiate prenatal care before week 13 and that the higher levels of early initiation of care persisted for at least 15 months and likely more than 24 months after the incentives ended. These results are consistent with a model of providers who face a fixed cost to changing their clinical practice routines, i.e.

20
# **Figure 2. Emerging Economy Exports Affected by Foreign-Imposed TTBs, 1995-2011 (cont.)**

<!-- Start of picture text --> percent Kazakhstan percent Malaysia<br>50 2<br>45 1.8<br>40 1.6<br>35 1.4<br>30 1.2<br>25 1<br>20 0.8<br>15 0.6<br>10 0.4<br>5 0.2<br>01995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11 01995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11<br>Pakistan Thailand<br>percent percent<br>16 6<br>14 5<br>12<br>4<br>10<br>8 3<br>6 2<br>4<br>1<br>2<br>0 0<br>1995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11 1995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11<br>Ukraine Vietnam<br>percent percent<br>25 16<br>14<br>20<br>12<br>15 10<br>8<br>10 6<br>5 4<br>2<br>0 0<br>1995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11 1995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11<br>percent Other emerging economy exporters<br>2<br>1.8 Exports to all economies subject to TTBs in effect<br>1.6<br>1.41.2 Exports to G20 High Income economies subject to TTBs in effect<br>1<br>0.8 Exports to G20 Emerging economies subject to TTBs in effect<br>0.6<br>0.4<br>0.2 Exports to all other economies subject to TTBs in effect<br>0<br>1995 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11<br><!-- End of picture text --> Notes: Shares of nonoil exports, constructed by the author with policy data from Bown (2012) and trade-weighting with HS-06 import data from UN Comtrade via WITS, following Appendix equation (A2).

24
For any given location, these means constitute our point estimates of welfare measure, while the standard deviations are the standard errors of these estimates.

# **Data and Implementation**

# **<u>Data</u>**

The technique combines data from the 2002 Azerbaijan Household Survey (AHBS 2002) and the 1999 Census collected by the State Statistical Committee of Azerbaijan Republic (Goskomstat). The Census covers around 1.7 million households containing 8 million individuals<sup>8</sup> . Administratively Azerbaijan has 9 economic regions, 73 rayon and 4,500 villages. Between village and rayon level there is an additional layer of administrative units, usually combining 3-5 villages together. It has been possible to combine the Census data and AHBS at the village level. The present analysis is limited to the 65 rayon, as it was not possible to include rayons in the occupied zone.

The AHBS 2002 survey covers 8,157 households and 33,000 individuals. The survey provides detailed information on a wide range of topics, including food consumption, non-food consumption, labour activities etc. The survey design incorporates stratification by region (economic zones and urban and rural strata). As has been previously mentioned in the main part of the paper, the HBS in its current format and sample design it is relatively new to the SSC. Since 1999 a group of international technical experts have been working on improving the HBS design in order to produce nationally representative data (Marnie et al. 2001). In designing the new survey, the team has attempted to rectify the faults of the old HBS, while limiting the additional human and financial resources required, since the survey has to be sustainable for the future. For these reasons the new HBS adopts a full quarterly rotation of households. The interviewers, instead of being involved in the collection of data from the same household over a

> 8 We consider the present population as it has been the population considered for the sample design of the Household Budget

34