rafmacalaba/datause-encoder-data huggingface dataset:
between young and adult women (Figure 4). Although the magnitude of the loss is small in terms of GDP growth rates, it is large in terms of foregone earnings. The PPP adjusted annual income loss is equivalent to US$646 million in Ethiopia (Table 2).

If young women had inactivity rates similar to those of young men, annual GDP growth rates would be up to 4.4% higher (Figure 7). Annual GDP growth rates in India, Nigeria, and Paraguay would be 4.4, 3.5, and 3.3 percent higher if girls were as economically active as boys (Figure 7). This is equivalent to almost US$165 billion (PPP adjusted) in India, for example (Table 2). In South Africa, where the gender differential in inactivity rates is small, the gains to greater economic activity of girls is much smaller, though it still exceeds US$3.7 billion.

The gender gap does not always incur higher opportunity cost than the age gap. In Bangladesh, Brazil, India, and Paraguay, the gains are much larger if girls’ inactivity rates were more similar to those of boys than of adult women since the gap in inactivity rates is larger between the sexes (within age) than the within-sex between-age gaps. While in the African countries in the sample, if girls had the same (lower) inactivity rates as adult women, the economies would enjoy larger gains than if the goal were to reduce girls’ inactivity rates to those of boys.

Accounting for the value of housework does not significantly change these estimates for those countries in which data are available. Data from Brazil and India allow us to adjust the opportunity cost of inactivity estimates to account for the productive value that home-based work generates. Such adjustments to the cost of inactivity include a proxy for the value of home-based production activities for young women. However, this decrease in the cost of inactivity is not considerable. For example, accounting for home-based production decreases the cost of inactivity of Brazil by 14% - thus reducing the losses relative to women’s employment from 1.2% to 1.0% of annual GDP - and that of India by 19% (a reduction of the annual GDP figure from 1.6% to 1.3%).

Turning to ―joblessness‖ rates, where we drop students from the inactivity rate, the cost of female youth joblessness – relative to that of adult women – falls to zero or is negative for most of our sample (Figure 6). In every country, adjusting the girls’ inactivity rate for the lower-bound school attendance estimate results in joblessness rates 17
and as they manifest themselves in the BEEPS surveys. In Sections IV and V, we analyze the evidence on convergence in two dimensions of the business environment: competition and financing. Section VI looks at how firms have responded in terms of restructuring. Section VII concludes.

# **I. Sample description, country classification and benchmarking**

The Business Environment and Enterprise Performance Surveys (BEEPS) have been conducted by the World Bank and EBRD since 1999. As the name suggests, the focus of the interviews with firm managers is the business environment in which firms are operating, but the data collected also include key figures about the firm, including sales, inputs, and growth. Most of the data gathered have come from three waves of surveys – 1999, 2002 and 2005 – implemented in nearly all the transition countries of Central and Eastern Europe and the former Soviet Union. The BEEPS were extended in 2004 and 2005 to include a range of comparator countries from Western Europe and East Asia.

Survey samples were constructed by random sampling from a national registry of firms or equivalent, with oversampling of some additional categories of firms to ensure reasonable subsample sizes. The firms covered are drawn from industry and services,<sup>3</sup> and, like the population of firms in countries around the world, are mostly SMEs (see Table II.1). A majority of the firms surveyed in the transition countries (60% in 1999, rising to 75% in 2005) are new private sector firms, i.e., they were private from the point of startup. Privatized firms make up about 15-25% of the sample, and the remaining 1015% were state-owned enterprises (SOEs). The shares of both privatized and SOEs in the BEEPS transition samples have been falling over time. The samples from the nontransition market economy comparator countries include very few SOEs and privatized firms, which means that our benchmark is the market economy private sector.

> 3 A small number of firms in agriculture, fishery, forestry as well as in power generation in the 1999 BEEPS survey are classified in this paper as manufacturing.

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objections is that the requirements could result in a number of different excises with different rates and operational rules. As a consequence, operation would be seriously complicated.

Fourthly, the requirements would lead to rejection of application of excises to certain commodities which are universally regarded as desirable for taxation and 'o have justification on economic efficiency grounds (alcohol, tobacco). The use of ad valorem rates may be contrary to the desire to relate the tax to quantities consumed rather than to vall A major implication of these conclusions is that an attempt to use a large number of separate excises, disaggregated by a particular form of the commodity or service, would be operationally very difficult.

# Differences Armong Families

Even if an excise system can be made progressive, there is still an important disadvantage from an equity standpoint, particularly with the tiaditional excises. The tax burden relative to income will vary greatly among families depending on whether or not the particular commodities are used in the family. Relatively heavy taxation of families in which one or more members smoke cigarettes may be justified on economic efficiency grounds, but can be seriously questioned on equity grounds.

# **THE CHOICE BETWEEN AD VALOREM VS SPECIFIC RATES**

A major issue with regard to excises is the choice between ad valorem and specific rates. 10 The issue is particularly important with the traditional excises and motor fuel. For most other excises the use of ad valorem rates is almost essential because of the problems of

> 10J. A. Kay and M. J. Keen, The Structure of Tobacco Taxes in the European Community (London: Institute for Fiscal Studies, 1S82); Cnossen, Excise Systems, op. cit., pp. 104-05.
ambiguity is left unresolved. Third, our results underline the importance of staying with the same design if the aim is to make comparison over time. Whatever the preferred design is, changes in design may result in changes in employment statistics even when no actual changes occurred. Finally our findings provide a base for a costbenefit analysis.<sup>19</sup> If the detailed self-reported module is best practice – as recommended by ILO guidelines and accepted in this paper by adopting it as a ‘benchmark’ – then we can assess what implications the use of less expensive approaches, like response by proxy or using a shorter module, has. The results suggest that for some indicators it may be acceptable to take short cuts, while for others the price paid in measurement error is probably quite high.

> 19 The cost implications of the design are mainly in terms of length of field work (and only very marginally the length of printing questionnaires and the data entry) through more days required in each sample village. Unfortunately we could not measure this directly in this experiment because it was part of a larger survey experiment with a consumption diary component, and we cannot isolate the costs related to the labor module. However, a back-of-the envelope calculation teaches us that to complete self-reports (and track down each adult), a team that otherwise would finish a survey in 2 days in the village will need 1 or 2 more days, implying 33-66% extension of the field work and corresponding increase in the budget.

33
_Figure 15: Female labor force participation rates (2017)._ <!-- Start of picture text --> Timor‐Leste<br>Malaysia<br>Philippines<br>Indonesia<br>Mongolia<br>East Asia & Pacific (excluding high income)<br>Thailand<br>China<br>Papua New Guinea<br>Vietnam<br>Myanmar<br>Cambodia<br>Lao PDR<br>0 10 20 30 40 50 60 70 80 90<br><!-- End of picture text --> Source: International Labour Organization, ILOSTAT database. Data retrieved in March 2017.

34
and EMDEs (Figure 7).<sup>6</sup> The 2009 recession was particularly severe for the United States whereas the U.S. economy experienced a mild recession in 2001 following the burst of the "dot com" bubble of the late 1990s. In the four quarters leading up to the last two U.S. business cycle troughs, other advanced economies also experienced a decline in the cyclical component of their GDP of, respectively, 0.5 and 4 percent, while their subsequent recoveries have been sluggish. Among EMDEs, slower activity was also observed around these two cyclical troughs.

Concordance statistics illustrate the degree of synchronization between the phases of the U.S. business and financial cycles and those of other economies. Business cycles are more highly synchronized than financial cycles: other countries tend to be in the same business cycle phase (specifically, troughs, peaks, expansions and downturns) with the U.S. cycle roughly 80 percent of the time. While the degree of synchronization of financial cycles with the U.S. financial cycle is lower than that of business cycles, they are quite often in the same phase—about sixty percent of the time for credit, housing, and equity price cycles (Figure 7). While it is difficult to establish empirically whether the U.S. economy leads business and financial cycle turning points in other major economies, recent research indicates that the United States appears to influence the timing and duration of recessions in a number of other major economies (Francis et al. 2015).

# **4 Spillovers from the United States to the global economy**

Developments in the U.S. economy have significant impacts on the global economy. Shocks to the U.S. economy transmit to the rest of the world through the range of channels discussed above. An acceleration in U.S. activity can lift growth in its trading partners directly, through an increase in import demand, and indirectly, by strengthening productivity spillovers embedded in trade.<sup>7</sup> Given its sizable role in global commodity markets, an acceleration in U.S. activity tends to lift global commodity demand and raise prices. This supports activity and eases balance of payments pressures in commodity exporters. Financial market developments in the United States may have even wider global implications. Changes in U.S. policies could therefore be expected to affect domestic activity and generate wide-ranging cross-border spillovers through real and financial channels.

> 6Two U.S. business cycle peaks (March 2001 and December 2007) and two U.S. business cycle troughs (November 2001 and June 2009) are identified since 2000 by the NBER’s Business Cycle Dating Committee.

> 7For a detailed analysis of the intensity of business cycle linkages between the United States and other countries, see Dées and Vansteenkiste (2007); Stock and Watson (2005); Kose (2003); Kose, Prasad, and Terrones (2004); Jansen and Stokman (2004); Eickmeier (2007); IMF (2007); and Roache (2008).

13
17 Today’s post‐financial crisis advanced countries vary greatly in terms of their underlying dynamism and need/ability to absorb new workers. It is perhaps not surprising that a country such as Germany, which has low unemployment, is aging rapidly, is competitive and growing smartly, runs a balanced budget and a large current account surplus has been more open to the prospect of receiving refugees than others, while struggling Italy has not, despite exhibiting even more unfavorable demographic trends than Germany (see chart 3).

It should be noted that, while the inflow of refugees can promote faster GDP growth, that will not be necessarily reflected in the higher growth of GDP per capita, which many would consider to be the more relevant measure of welfare. However, the expansion of the capital stock implied by the arrival of new workers may not be the only way that immigration boosts economic growth. Micro‐level studies suggest that migrants may also induce accelerated productivity growth by providing a disproportionate share of entrepreneurs and innovators, by taking on jobs or moving to localities where native workers are reluctant to go, and by providing a source of labor services that respond more readily to the business cycle (Orhan & Senyücel 2015). None of these benefits – except for the initial demand‐expanding stimulus to demand – are likely to accrue if the refugee is forced or encouraged to return early in the cycle of his or her economic integration.

As has been extensively argued in OECD, World Bank and IMF reports, policies in advanced countries towards immigration, including towards refugees, should also take into account the degree to which immigration can help offset unfavorable demographic trends. This consideration is especially important in Europe, where the population is aging rapidly. The old‐age dependency ratio – the ratio of people over 65 and those of working age – is projected to rise rapidly from 30 in 2015 to 55 in 2050. Charts 2 and 3 (from IMF 2016) show projected population and net migration for the EU28 and for Italy, where population aging is advancing most rapidly, and where the natural change in the population turned negative back in 2010. According to United Nations Population Division projections (medium variant), Italy’s 20‐64 cohort, the population of working age, will decline by 10% (!) over 2015‐2030.

# **Chart 2 EU 28 Population Changes (Millions)**
Hendryx, M. and M. M. Ahern (2009). Mortality in Appalachian Coal Mining Regions: The Value of Statistical Life Lost. Public Health Reports, Vol. 124, No. 4, pp. 541-550.

- Hendryx, M., K. O’Donnell and K. Horn (2008). Lung cancer mortality is elevated in coal-mining areas of Appalachia, Lung Cancer, Vol. 62, No. 1, pp. 1–7.

- Hoeve, J.E.T and M. Z. Jacobson (2012). "Worldwide health effects of the Fukushima Daiichi nuclear accident". Energy & Environmental Science. Vol. 5, No. 9, pp. 8743 -8750.

- Hosgood III, H. D., H. Wei, A. Sapkota, I. Choudhury, N. Bruce, K. R. Smith, N. Rothman and Q. Lan., 2011. Household coal use and lung cancer: systematic review and meta-analysis of case-control studies, with an emphasis on geographic variation. International Journal of Epidemiology, Vol. 40 (3), pp. 719-728.

- Hu, G., Y. Zhou, J. Tian, W. Yao, J. Li, B. Li and P. Ran, 2010. Risk of COPD From Exposure to Biomass Smoke: A Metaanalysis. Chest, Vol. 138 (1), pp. 20-31.

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Jackson, RB, Avner Vengosh, JW Carey, RJ Davies, TH Darrah, F. O’Sullivan and G. P ́etron (2014). The Environmental Costs and Benefits of Fracking. Annual Review of Environmental Resource. Vol. 39. Pp. 327-362.

- Kirk R. Smith, Howard Frumkin, Kalpana Balakrishnan, Colin D. Butler, Zo ̈e A. Chafe, Ian Fairlie, Patrick Kinney, Tord Kjellstrom, Denise L. Mauzerall, Thomas E. McKone, Anthony J. McMichael, and Mycle Schneider (2013). Energy and Human Health. Annual Review of Public Health, Vol. 34. Pp.159–188.

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29
responded positively to private sector involvement and regulation; while the quality of service improved with private sector involvement.

The final group of tests (type III) are those in which reform was correlated with economywide objectives. Improvements in sector performance could facilitate improvements in GDP and the HDI, but links would be indirect.

_Emissions of CO2 per kWh_ have not been a key part of sector reform but some studies tested whether reform led to decreased emissions. One study found that reduced emissions were not linked to unbundling or private sector involvement but were linked to regulation and competition.

_GDP per capita and the HDI_ were expected to increase as a result of sector reform but only two studies tested for this effect. One study found that private sector/competition interaction was significant, but the other found that none of the four policy dummy variables was significant. A similar negative result was found with respect to the HDI.

The study by Gassner et al. (2009) disaggregated private sector involvement into sub-categories by type of private sector contract. Nine performance indicators were each regressed on four dummy variables for type of private sector involvement (full divestiture, partial divestiture, concession, lease or management contract), a utility specific fixed effect, and a time trend. No other reform variables were included, nor any non-policy variables. Because this is the only study that provides this level of disaggregation for private sector participation, it is valuable to compare the results for the separate forms of contract with the results obtained with no disaggregation by contract type. The study also tested for the impact of any type of private sector participation. Table 8 reports the significant coefficients.

Table 8: The effect of private sector participation on performance by type of contract

|**Performance indicator**|**Any type of**<br>**private sector**<br>**participation**|**Full**<br>**divestiture**|**Partial**<br>**divestiture**|**Concession**|**Lease or**<br>**management**<br>**contract**|
|---|---|---|---|---|---|
|Residential connections|N|N|N|Y:↑|N|
|Electricity sales per connection|N|Y:↑|N|N|N|
|Employment|Y:↓|Y:↓|Y:↓|N|N|
|Electricity sales per worker|Y:↑|Y:↑|Y:↑|N|N|
|Residential connections per worker|Y:↑|Y:↑|Y:↑|N|N|
|Residential access|N|N|N|N|N|
|Collection rate|Y:↑|Y:↑|Y:↑|Y:↑|N|
|Distribution losses|Y:↓|N|Y:↓|N|N|
|Supply disruptions|N|N|N|N|N|

_Source_ : Gassner et al. (2009) Lease or managements contracts were not associated with performance improvement of any of the indicators, suggesting that the short-term nature of this private sector involvement did not make it worthwhile to spend time or money on improving the performance of the utility. Concessions 40
The Ricardian results will consequently have these distortions embedded in the results. For example, if a country mandates that a fraction of cropland be devoted to a certain crop, one may well see more of that crop in that country than elsewhere. We can control for such effects using country dummies. In general, we prefer not to place dummies unless there is evidence of a distortion. Nonetheless, if future decision makers eliminate these subsidies or introduce new ones, the empirical results may no longer hold. Policies that differ across countries could contribute to some of the differences in farm net revenue.

# **3. Data and empirical analyses**

The data for this study were collected by national teams. In each country, districts were chosen to get a wide representation of farms across climate conditions in that country. The districts were not representative of the distribution of farms in each country as there are more farms in more productive locations. In each chosen district, a survey was conducted of randomly selected farms. The sampling was clustered in villages to reduce sampling costs.

A total of 9597 surveys were administered across the 11 countries in the study. The number of surveys varied from country to country. (For more information on the survey method and the data collected see Dinar et al. 2006.) Not all the surveys could be used. Some farms did not grow crops (they only raised livestock). Some surveys contained incorrect information about the size of the farm, cropping area or some of the farm operating costs. Impossible values were treated as missing values. It is not clear what the sources of these errors were but field and measurement errors are most likely. They may reflect a misunderstanding of the units of measurement, they may reflect a language barrier, or they may be intentional incorrect answers. The final number of useable surveys is 9064 and their distribution by country is shown in Table 1.

Data on climate were gathered from two sources. We relied on temperature data from satellites operated by the Department of Defense (Basist et al. 2001). The Defense Department uses a set of polar orbiting satellites that pass above each location on earth between 6am and 6pm every day. These satellites are equipped with sensors that measure surface temperature by detecting microwaves that pass through clouds (Weng & Grody 1998). The precipitation data come from the Africa Rainfall and Temperature Evaluation System (ARTES) (World Bank 2003). This dataset, created by the National Oceanic and Atmospheric Association’s Climate Prediction Center, is based on ground station measurements of precipitation. The temperatures for each country in the sample are shown in 9
# **5.1 Average program impacts on refugees pooling survey rounds**

Table 4 presents the estimated treatment effects on refugees for the pre-specified primary outcome measures, as well as statistically significant effects on other outcomes.

In terms of primary outcomes, the estimated treatment effect on the housing quality index is positive and moderate in size, at 0.31 standard deviation units, though not statistically significant at traditional confidence levels. Regarding rental payments, there is a significant reduction in households’ out-of-pocket housing expenditures of 82.05 USD (SE 32.07) and the estimate survives the False Discovery Rate (FDR) multiple testing adjustment (q-value=0.07). This measure was reliably collected at the endline survey when the subsidy itself was ending for some households but the program’s contractual rental level controls should still have been in place. Taken together, the two findings indicate that the program at least partly achieved some of its main proximate objectives of improving housing quality and reducing the rental burden for refugee households, although the housing quality estimate is suggestive. As we are unable to directly measure the reduction in out-of-pocket housing expenditures during the midline survey (as noted above), the endline estimate likely understates the true program benefit to treatment households in terms of reduced rental payments.

In a central finding of the study, we next show that the average estimated program effect on consumption across all survey rounds is small and not statistically significant (Table 4). Specifically, across all rounds for which data are available (which varies across the measures, see notes in Table 4), there are no significant impacts on household food consumption nor log total household consumption expenditures. Likewise there is no significant effect on respondent depression as assessed using the widely used CES-D scale. It appears that a substantial year-long housing subsidy plus shelter upgrade was not sufficient to meaningfully improve these key living standards measures, although it is worth noting that, as with the housing quality effects, the relatively weak first stage increases standard errors on these IV estimates. Despite this, these estimated null effects are still fairly precise: the associated standard errors suggest that an effect of 0.16 log points on 21