rafmacalaba/datause-encoder-data huggingface dataset:
collection was finished.<sup>16</sup> In total, we received useable data from 192 women (77 percent of the original sample).

Overall, the women who appear in our dataset tend to be more informal than would be the case of streetwalkers or women who work out of brothels. Most of the women in our sample find clients in bars, nightclubs, or hotels, and many see clients in the client’s home (or, less frequently, in their own home). The vast majority do not self-identify as sex workers: instead, most refer to themselves as “survivors,” women who engage in transactional sex to make money to live.

# B. Diaries and Other Survey Modules

The primary source of data we use are daily “diaries” which were kept by the sex workers. The diaries were essentially pre-printed surveys with questions on income, expenditures (across a number of different categories), and the shocks that were encountered that day. The diaries also include details on each encounter with a client, including the specific sexual activities performed, the price, and whether a condom was used.<sup>17</sup> As discussed previously, the main outcome in this paper are the transfers received by sex workers from clients. On a separate page from the sexual behavior with clients, women recorded all the other sources of in- and outflows that they received in a day. These included gifts and loans from friends and relatives, ROSCA payouts, and other sources of income (such as other regular work, or irregular income sources such as the sale of livestock or of animal produce). On this page, women recorded transfers from clients in four separate categories: cash, rent,

> 16. In Robinson and Yeh (2011), we find no statistically significant differences in observable characteristics at baseline between the 49 women who dropped out and other women.

> 17. Some versions of the diaries do not differentiate between unprotected vaginal and anal sex, so we aggregate them together in this paper.

14
We address this concern by including in equation (1) interactions of FemSharest0 with a set of district-level time-variant variables, which may plausibly affect the productivity of plants with smaller or larger shares of female employees differently. These district level controls aim to reflect changes in public sector funding, in overall infrastructure, and in education outcomes. Inclusion of interactions will purge such confounding effects from our coefficient of interest. Insignificant coefficients on interactions between FemSharest0 and district-level controls would signal that firms with a higher/lower share of female workers do not benefit differently from district level changes in public spending, infrastructure and education. Specifically, we estimate: where vector ΤZdt includes three variables: total government expenditure per capita, a measure of road infrastructure and a measure of the quality of education in the district, as described in Section 3.1.

Table 8 presents the estimates from equation (4). Coefficients in columns (I), (II), (V) and (VI) suggest that there is no variation in the impact of government expenditure or road infrastructure on TFPR and TFPQ, depending on the share of female workers per firm. Notably, the coefficient on the interaction between female share and an indicator of education quality is statistically significant. Plants with a higher share of female workers are able to take greater advantage of educational attainment in their districts. This is not surprising: women out of labor force in Indonesia are generally higher educated than men who remain out of labor force. Thus, by employing more women firms may be able to tap into greater pool of highly qualified potential workers. Although growth in overall level of education may be positively correlated with preschool expansion, inclusion of this additional covariate barely changes the magnitude of our main coefficient of interest – the change is less than 0.1 percentage point.

# 5. Channels

We explore two possible mechanisms that can lead to the observed impacts of preschools on plant productivity. First, following Hsieh et al. (2019) we check whether the observed increase 15
Table 1: Cambodia Domestic Government Revenues, 2019

|Source|Amount<br>(billion<br>KHR)|Percent<br>of GDP|Percent of<br>Government<br>Revenue|Included<br>in CEQ<br>analysis|
|---|---|---|---|---|
|**Domestic Revenues (A+B)**|27,730|25|100||
|**A. Central Government Revenue (I+II+III)**|25,576|23|92||
|**I. Tax Revenue**|22,053|20|80||
|**Direct taxes of which**|5,045|5|18||
|Profit tax|4,197|4|15|n.a.|
|Payroll tax|848|1|3|Yes|
|Tax on interest, royalties, and dividends|--|--|--|No|
|Land and property|--|--|--|Yes|
|**Indirect taxes of which**|14,095|13|51||
|VAT (domestic and on imports)|7,410|7|27|Yes|
|Excise duties (domestic and on imports)|6,478|<br>6|23|Yes|
|Others|207|0|1|Yes|
|**Taxes on international trade**|2,913|3|11|n.a.|
|**II. Non-tax revenue**|3,342|3|12|n.a.|
|**III. Capital revenue**|181|0|1|n.a.|
|**B. Provincial revenue**|2,153|2|8|n.a.|

## Source: MEF.

Note: Social Security Contributions revenue (96.4 billion KHR as of 2018) are recorded under the revenue of the National Social Security Fund. Hence there is no record under Budgetary Central Government Level.

# _Indirect taxes_

Value added tax (VAT) is the largest component of indirect taxes. It amounts to 27 percent of domestic government revenues. VAT is applied to taxable goods and services at a 10% flat rate. Exempted from VAT are public postal services, hospital, clinic, medical and dental services, the sale of medical and dental goods, the services of transporting passengers using the state-owned public transportation system, educational services, water and electricity, raw agricultural products and liquid and solid waste disposal services.

Excise tax is the second largest component of indirect taxes amounting to 17 percent of domestic government revenues. Excises are imposed on the importation or domestic production and supply of certain goods and services with various tax rates including cigarettes, cigars, beer, petroleum products, cars, motorcycle, telephone services, transportation services, hotels, and entertainment services.

# _Direct taxes_

As is the case in most countries, the fiscal system in Cambodia has various types of direct taxes levied on income or wealth. The system of direct taxes and contributions covers taxes on income, profits, capital gains and property (further details are provided in the Technical Appendix). Direct taxes in Cambodia represent 18 percent of domestic government revenues in 2019, of which corporate income tax and salary tax account for the largest components.

6
47 skilled workers at current salaries; it is, however, difficult to recruit the higher-skilled Senegalese and non-African employees. Managers cite as the principal obstacles the shortage of welltrained Senegalese and the constraints of existing regulations that make it less attractive for expatriates to accept employment. Salaries are not considered to be a problem. Interestingly, similar results are reported by Pfeffermann (1968) from his 1963 survey of the managers in 22 firms: When asked what was the major problem with the African labor force, _45_ percent of the managers interviewed by Pfeffermann answered "qualifications." An important point to note is that whereas most employers complain about the lack of skills in the labor force, relatively few provide training. We found that only one-third of the workers in the 17 fims we surveyed had received some training in the firm. Comparing this figure with Pfeffermann's finding that 42 percent of the firms in 1963 had manpower training schemes (Pfeffermann, 1968, p. 285), it appears that the amount of training provided by most firms has been declining. It is of course impossible to draw a firm conclusion in this respect because of the potential differences in the two samples.

In assessing the perceived lack of skills in the labor force, one of course has to take into account the extent and quality of the educational system. Available data indicate that the education budget has increased from less than 1 percent of GDP in 1960 to 5 percent of GDP in 1984. While this increase is impressive, the net enrollment rate in primary education is still only 40 percent and is expected to decline in view of the containment of public expenditures and the 2.9 percent annual population growth rate. This, and the fact that only 40 percent of students entering primary schools graduate, suggests that the government's objective to achieve universal primary education by the end of the twentieth century may be too ambitious. In addition to suffering from low enrollments, Senegal's system of primary education is reported to be exceedingly academically oriented, at the expense of practical training which might facilitate access to productive employment. Our interviews with workers revealed many cases of illiteracy, thus also providing evidence that the educational background of many workers is very limited.

As mentioned previously, it appears that many workers were originally recruited not through the Labor Service but through other channels. The managers simply 'regularized' the workers
# **The Role of Imports for Exporter Performance in Peru**

# **Martha Denisse Pierola**<sup>**a**</sup>

# **Ana Margarida Fernandes**<sup>**b**</sup>

**Thomas Farole**<sup>**c**</sup>

# **JEL Classification codes** : F14, O1.

**Keywords:** exporter growth, exporter diversification, firm-level data, imported inputs.

a Martha Denisse Pierola. The World Bank. Development Research Group. Email: mpierola@worldbank.org.

b Ana Margarida Fernandes. The World Bank. Development Research Group. Email: afernandes@worldbank.org. c Thomas Farole. The World Bank. Email: tfarole@worldbank.org.

* Financial support from Macro and Fiscal Management Global Practice, Latin America Region, is gratefully acknowledged. This paper was prepared as a background paper for the Peru Flagship Study for the Annual Meetings 2015 _How to Avoid the Middle Income Trap? Sustaining High and Equitable Growth in Peru_ . The authors would like to thank Norman Loayza, Ekaterina Vostroknutova, and Javier Roca for helpful discussions. We also thank Aldo Bortoluzzi for his invaluable help with the customs data and Reyes Aterido, Trang Tran, and Cinthya López for help with other data. We are grateful for the support of the IFC and the Governments of UK, US, and Canada through the Investment Climate Impact Program.  Research for this paper has in part been supported by the World Bank’s Multidonor Trust Fund for Trade and Development and the Strategic Research Program on Economic Development.
'*****Household Income and Savings***** IDGSS.APPEND Y_hh=PX*XS -INDTAX +(EXR*TR_hh_row)'Indirect production taxes are paid to the government IDGSS.APPEND SAV_hh=mps_hh*(1-ytx_hh)*Y_hh IDGSS.APPEND CONS_hh=(1-mps_hh)*(1 -ytx_hh)*Y_HH/PQ '*****Aggregate Savings***** IDGSS.APPEND SAVTOT= SAV_hh + (EXR*FSAV) + SAV_gov '*****System Constraints and Closure***** 'Full capacity is assumed so that XS is made exogenous 'Domestic Demand Constraint Implicitly defined through XD 'Material Balance for Composite Consumption Good Implicitly defined through QQ 'Fiscal Balance IDGSS.APPEND SAV_gov=(Y_gov - PQ*CONS_gov) 'Balance of Payments in Local Currency IDGSS.APPEND EXR*FSAV=(PM*QM/(1 + tm) - PE*XE -(EXR*TR_hh_row)) 'Investment-Savings Balance IDGSS.APPEND INV=SAVTOT/PQ 'Further Constraints 'Private and Government Consumptions Remain Fixed '==========Calibration and Initialization========================================== 'Declare Variables FOR %VR CONS_gov CONS_hh XD EXR FSAV HHTAX INDTAX INV mps_hh omega_x PD PDT PE PM PQ PWE PWM PX QQ QM SAV_gov SAV_hh SAVTOT sigma_q TARIFF TD TE TM TR_hh_row XE XS Y_gov Y_hh ytx_hh MT 'MT stands for imports inclusive of tariffs to use in calibration SERIES %VR NEXT EXR=9311 'LCU (Rupiah) per US$, period average (from LDB on line) FSAV=IDMACSAM(5,6)/EXR te=0 PM=1 XD=IDMACSAM(1,2) SERIES ITX=IDMACSAM(4,1) td=ITX/(XD-ITX) PD=1/(1+td) PDT=PD*(1+ td) INDTAX=td*PD*XD QM=IDMACSAM(6,2) + IDMACSAM(4,2)'Imports inclusive of tariff TARIFF=IDMACSAM(4,2) tm=TARIFF/(PM*QM - TARIFF) PE=1 PWE=PE/((1+te)*EXR) PWM=PM/((1+ tm)*EXR) PQ=1 PX=1 XS=IDMACSAM(1,7) TR_hh_row=IDMACSAM(3,6)/EXR Y_hh=(PX*XS -INDTAX+(EXR*TR_hh_row)) HHTAX=IDMACSAM(4,3) XE=IDMACSAM(1,6) ytx_hh=HHTAX/Y_HH QQ=IDMACSAM(2,7) INV=IDMACSAM(2,5) Y_gov=TARIFF +INDTAX + HHTAX -(te*PWE*EXR*XE) CONS_gov=IDMACSAM(2,4) 31
fieldwork, however, there were difficulties locating the girls listed in the school records, and most of the recent drop outs had either moved away or were not living with their parents anymore and were thus ineligible for interview. The sampling target of 20 per school was therefore not attained in many of the smaller schools, and where possible more than 20 girls were sampled in order to help preserve power. All in all, the median number of girls surveyed per school in the baseline household survey is 18, and recent drop outs were underrepresented in the household survey sample (3% of the baseline sample compared to 13% of all girls last enrolled in Grades 5 or 6 at some point during 2013-2015 across all 173 schools). There was no difference in the total number of girls interviewed in the baseline household survey, or the share of recent drop outs in the household survey sample, across treatment arms, however.<sup>16</sup> For transparency, the main analysis reported in this paper is carried out at the school level (i.e., averaging variables at the school level), and does not apply any sampling weights so that each school is weighted equally whatever the number of girls interviewed or observed during the spot checks. In robustness checks reported in Section IV, we also repeat the analyses giving each school a weight proportional to the size of its potential EP2 intake for 2016 (based on school enrollment data for 2013, 2014 and 2015 and thus prior to our experiment).

_Timing_ . The Mozambican school year runs from February to December. We collected a baseline survey between the end of the 2015 school year and the start of the 2016 school year, and a follow-up survey one year later (See Figure 1). Each school received an initial visit by the implementation NGO, a locally well-known development organization called Magariro. School staff in all grade 6 in 2015 (“enrolled in 2015” list) or (ii) were enrolled last in grade 5 or 6 either in 2013 or 2014 (“recent drop-outs” list).

16 The maximum difference between any two experimental arms is 0.8 girl (tstat: 0.72) for the number of girls interviewed and 1.4%-points difference in the share of recent drop outs (t-stat: -1.26).

19
The sharp result that comes out of this simple example follows from three assumptions. First, the income shock is saved. Second, investing in foreign capital is not an option for the country. Third, the marginal unit of wealth is allocated among assets as the average one is. We maintain the first two assumptions throughout the paper without (excessive) apologies. The first assumption is a basic tenet of consumption-smoothing models of savings. Despite some empirical failures of the simplest of these models, we feel the jury is still out regarding the relative importance of consumption-smoothing as a savings motive at the business cycle frequency that we focus on here.' The second assumption can be easily removed.<sup>2</sup> If we keep the other assumptions, a favourable income shock still leads to a current account deficit if and only if the share of domestic capital in the country's wealth exceeds one or, equivalently, if and only if foreign debt exceeds the stock of outward foreign investment. Otherwise a favourable income shock leads to a current account surplus.

The bulk of the theoretical effort of this paper is devoted to assessing the merit of the third assumption underlying our simple example, namely, that the marginal unit of wealth (savings) is invested in the same proportions as the stock of wealth. To do so, we construct a simple world equilibrium model in which productivity varies across countries and intemational borrowing and lending takes place to exploit good investment opportunities. In the model, we distinguish between production uncertainty and random changes in technology. In each date, some countries have "good" production functions that exhibit high average productivity, while other countries have "bad" production functions that exhibit low average 1 The importance of consumption-smoothing depends on the frequency of the data one is analyzing. It is obviously important for the analysis of quarterly data (most people spend more than they eam over Christmas and other holidays, and somewhat less than they earn in other times), and almost as surely is a bad theory for understanding savings rates over a quarter of a century. See Deaton (1992) for a survey of evidence on intertemporal models of savings. 2 Moreover, this assumption is consistent with the strong home equity preference in OECD economies that has been documented by French and Poterba (1991) and Tesar and Werner (1992). Lewis (1995) surveys alternative explanations for this phenomenon.

2
**Figure IV.2 Secondary market spreads on sovereign debt (June 1997 - February 1998)**

<!-- Start of picture text -->
*000  L:  T":  ::"'<"'<br>t5o:~~~~o  2,  0.0  00  00  000  JO  .<br>- - --  --  - --  - .-  - ~  --.<br><!-- End of picture text -->

Source: Bloomberg Prior to the crisis, stock markets among South East Asian countries did not show extraordinary comovement. As noted, the stock price in Thailand had more or less monotonously experienced a decline since January 1996, cumulating to a loss of about 65% in real local currency terms by June 1997. Between January and June 1997, the Philippines and Malaysia had also experienced a decline in their stock markets, but of smaller magnitude, while Indonesia and Korea still registered increases in their stock markets of about 10%. Following the July 2 Thai crisis, the Thailand stock market initially rebounded strong, with a 25% increase in July. In the rest of East Asia, stock prices declined modestly during July. The comovement among stock prices in the region increased greatly, however, in August, as stock prices in South East Asian countries fell by about 25% and prices in Korea and Hong Kong declined (Figure IV.3). September saw a period of consolidation, with little change in stock prices across the region. During the period from mid-November to mid-January stock market declines continued in East Asia, with the exception of China and Taiwan (ROC).

51
# 7. **Performance of Pension Funds**

**Due to the conservative investment policy imposed on PFR-VEB, the return on the default option has been disappointing, but the returns of the NPFs and asset managers have not been satisfactory either** . Although NPFs’ information at the time of this report was only available for the period 20062008, at least for the years 2007-2008 the returns of the asset managers and NPF have not been significantly better than the fund managed by PFR-VEB (Figure 6). However, important differences in the returns of pension funds are expected in 2009. While in 2009 the real return of PFR-VEB was only 0.6 percent, the average real return of PFR-AM was 27.5 percent. These differences are related to the asset allocation, and reaffirm the argument about the need to improve the asset allocation of PFR-VEB.

Figure 6 Real Annual Returns of Pension Funds (2004-2009) (%) <!-- Start of picture text --> 30,00%<br>20,00%<br>10,00%<br>0,00%<br>2004 2005 2006 2007 2008 2009<br>-10,00%<br>-20,00%<br>-30,00%<br>-40,00%<br>PFR-VEB PFR-AM NPF<br>-50,00%<br><!-- End of picture text --> Source: FFMS

**Differences in the asset allocation, in particular the exposure to equity, explain the different performance of pension funds** . As shown in Figure 7, the PFR-VEB increased its participation in government securities from 80% in 2005 to 97 percent in 2008, but it was subsequently reduced to 80 percent as a consequence of the introduction of the enhanced portfolio. In the case of PFR-AM and NPFs, the asset allocation is more diversified and includes government securities, regional state securities, municipal securities, commercial bonds, equity and cash. In both cases, there is broad diversification among instruments. Although there are no major differences among the portfolio composition of PFRAM and NPFS, the liquidity needs in the case of PFR-AM in terms of cash seem to be higher than in the

25
# References

- [1] Aghion, P. and Howitt, P., 1992, A Model of Growth through Creative Destruction, Econometrica, 60(2), 323-351.

- [2] Akinbobola, T.O., and Saibu, M.O.O., 2004, Income Inequality, Unemployment and Poverty in Nigeria: A Vector Autoregressive Approach, Journal of Policy Reform, 7(3), 175-83.

- [3] Arrow, K.J., 1962, The Economic implications of Learning by Doing, Review of Economic Studies, 29, 155-73.

- [4] Aschauer, D.A. 1989a, Is public expenditure productive? Journal of Monetary Economics, 23(2), 177—200.

- [5] Aschauer, D.A. 1989b, Public Investment and Productivity Growth in the Group of Seven, Economic Perspectives, 13(5), 17-25.

- [6] Aschauer, D.A. 1989c, Does Public capital Crowd Out Private Capital? Journal of Monetary Economics, 24(2): 171—88.

- [7] Aschauer, D.A. 1998, The Role of Public Infrastructure Capital in Mexican Economic Growth, Economia Mexicana Nueva Epoca, 7(1), 47-78.

- [8] Aschauer, D.A. 2001, Output and Employment Effects of Public Capital, Public Finance and Management, 1(2), 135-60.

- [9] Ayogu, M.D., 1999, before Prebendalism: A Positive Analysis of Core Infrastructure Investment in a Developing Fiscal Federalism, African Development Review, 11(2), 169-98.

- [10] Badawi, A., 2003, Private Capital Formation and Public Investment in Sudan: Testing the Substitutability and Complementarity Hypotheses in a Growth Framework, Journal of International Development, 15(6), 783-99.

- [11] Bajo-Rubio, O., and Diaz-Roldan, C., 2005, Optimal Endowment of Public Capital: An Empirical Analysis for the Spanish Regions, Regional Studies, 39(3), 297-304.

- [12] Baltagi, H., and Pinnoi, N., 1995, Public Capital Stock and State Productivity Growth: Further Evidence from an Error Correction Model, Empirical Economics, 20, 351-59.

- [13] Barro, R.J., 1990, Government Spending in a Simple Model of Endogenous Growth, Journal of Political Economy, 98(5), S103-S125.

- [14] Barro, R.J., 1998, Notes on Growth Accounting, National Bureau of Economic Research Working Paper No. 6654.

- [15] Bartelsman, E.J., and Doms, M., 2000, Understanding Productivity: Lessons from Longitudinal Microdata, Journal of Economic Literature, 38, 569-94.

- [16] Benhabib, J., and Spiegel, M.M., 1994, The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country and Regional US Data, Journal of Monetary Economics, 32(3), 363-94.

- [17] Bernard, A., and Jensen, J.B., 1995, Exporters, Jobs and Wages in US Manufacturing: 197687, Brookings Papers on Economic Activity: Microeconomics, Washington D.C., 67-112.

- [18] Bernard, A., and Jensen, J.B., 1999, Exceptional Exporter Performance: Cause, Effect or Both?, Journal of International Economics, 47(1-), 1-25.

23