rafmacalaba/datause-encoder-data huggingface dataset:
**Table 10 Pooled OLS Estimation with Two Period Lag**

||Regulations|Finance|Entry|Time to<br>Export|Infrastructure|Property|
|---|---|---|---|---|---|---|
|RealGDP(PPP)|0.980|1.010|1.057|0.989|0.988|0.986|
||(0.031)***|(0.045)***|(0.039)***|(0.036)***|(0.036)***|(0.034)***|
|Log(Area)|-0.097|-0.113|-0.140|-0.096|-0.102|-0.108|
||(0.030)***|(0.049)**|(0.045)***|(0.039)**|(0.044)**|(0.041)**|
|Remoteness|-0.264|-0.431|-0.361|-0.340|-0.396|-0.429|
||(0.128)**|(0.208)**|(0.193)*|(0.171)**|(0.168)**|(0.178)**|
|Export Growtht,t-1|0.066|0.068|0.052|0.053|0.087|0.069|
||(0.073)|(0.090)|(0.078)|(0.077)|(0.077)|(0.085)|
|Size of Trade|0.115|0.081|0.085|0.096|0.091|0.101|
||(0.021)***|(0.033)**|(0.025)***|(0.024)***|(0.021)***|(0.022)***|
|log(TTRI)|-0.171|-0.426|-0.404|-0.345|-0.332|-0.330|
||(0.091)*|(0.129)***|(0.118)***|(0.100)***|(0.095)***|(0.112)***|
|log(MATTRI)|-0.136|-1.066|0.191|0.610|-0.550|-0.598|
||(0.045)***|(0.349)***|(0.188)|(0.337)*|(0.194)***|(0.186)***|
|log(MATTRI)*Indicator|0.181|0.252|-0.035|-0.241|0.331|0.078|
||(0.055)***|(0.102)**|(0.015)**|(0.099)**|(0.151)**|(0.032)**|
|Indicator|0.238|-0.200|0.005|-0.165|0.440|0.068|
||(0.080)***|(0.152)|(0.028)|(0.161)|(0.236)*|(0.044)|
|Constant|2.071|4.459|2.199|3.538|3.058|3.619|
||(1.416)|(2.143)**|(2.030)|(1.825)*|(1.630)*|(1.824)*|
|Observations|120|107|119|119|118|115|
|R-squared|0.971|0.947|0.958|0.965|0.964|0.964|

* Pooled OLS results. Export value at period _t_ is regressed on variables at period _t-2_ . Robust standard errors clustered by country are in parentheses. All regressions control for year fixed effects.*** p<0.01, ** p<0.05, * p<0.1.

20
# **The Effect of Height on Earnings: Is Stature Just a Proxy for Cognitive and Non-Cognitive Skills?**

Laurent Bossavie, The World Bank<sup>1</sup> Harold Alderman, International Food Policy Research Institute (IFPRI) John Giles, The World Bank Cem Mete, The World Bank JEL classification: J10, J70 Keywords: Nutrition, Skills and Education, Labor Earnings

> 1 Corresponding author: lbossavie@worldbank.org
- Levere, M., Acharya, G., and Bharadwaj, P. (2016). The role of information and cash transfers on early childhood development: Evidence from Nepal. Working Paper No. 22640, National Bureau of Economic Research.

- Macours, K., Premand, P., Schady, N., and Vakis, R. (2015). Experimental evidence from an early childhood parenting intervention in Nicaragua.

- Macours, K., Schady, N., and Vakis, R. (2012). Cash transfers, behavioral changes, and cognitive development in early childhood: evidence from a randomized experiment. 4(2):247–273.

- Macours, K. and Vakis, R. (2014). Changing households’ investment behaviour through social interactions with local leaders: Evidence from a randomised transfer programme. _The Economic Journal_ , 124(576):607–633.

- Macours, K. and Vakis, R. (2017). Sustaining impacts when transfers end: Women leaders, aspirations, and investments in children. In _The Economics of Poverty Traps_ , pages 325– 355. University of Chicago Press.

- Maluccio, J. A., Hoddinott, J., Behrman, J. R., Martorell, R., Quisumbing, A. R., and Stein, A. D. (2009). The impact of improving nutrition during early childhood on education among Guatemalan adults. _The Economic Journal_ , 119(537):734–763.

- Martinez, S., Naudeau, S., and Pereira, V. A. (2017). Preschool and child development under extreme poverty : evidence from a randomized experiment in rural Mozambique. Policy Research Working Paper No. 8290, The World Bank.

- Millán, T. M., Barham, T., Macours, K., Maluccio, J. A., and Stampini, M. (2019). Longterm impacts of conditional cash transfers: Review of the evidence. _The World Bank Research Observer_ , 34(1):119–159.

- Mischel, W., Shoda, Y., and Rodriguez, M. I. (1989). Delay of gratification in children. _Science_ , 244(4907):933–938.

31
Table 6: Observed relationships between Outvut and Eloyment, by Sector. 1970-80

|||GDP(")||Average A<br>Growth of|nnual<br>GDP(%)|Average An<br>of Employ|nual Growth<br>ment(%)|Employme<br>Elastici|nt/Output<br>tiesla)|
|---|---|---|---|---|---|---|---|---|---|
||1970|1975|1980|1970-75|1970-80|1970-75|1970-80|1970-75|1970-80|
|Agriculture(h)|41.5|56.3|58.7|6.3|3.5|0.8|-0.5|0.12|-|
|Mining|460.3|427.9|<br>398.7|<br>-1.4|-1.4|2.4|0.9|-|-|
|Manufacturing|129.2|157.6|162.9|<br>4.1|2.3|3.0|2.3|0.73|1.0|
|Construction|90.3|138.5|<br>79.1|<br>8.9|-1.3|0.9|-4.4|0.10|-|
|Transport|48.8|57.6|<br>56.5|<br>3.4|1.5|'-0.3|0.7|-|0.47|
|Services '|403.8|499.5|<br>554.2|<br>4.3|3.2|4.9|3.3|1.14|1.03|
|TOTAL|1173.9|1337.4|1310.1|2.6|1.1|2.8|1.0|1.08|d.91|

Notes: a) Millions of Constant 1970 Kwacha, market prices

- b) Excluding subsistence output and employment

- c) Includes import duties less imputed bank service charges

- d) Calculated by dividing average annual growth of employment by that of GDP, for each period and sector

Sources: GDP data: CSO, Konthly Digest of Statistics, various issues Employment data: Text, Table 5
Figure 6: PISA scores compared over time and with 16 and 17 year-olds <!-- Start of picture text --> 3A 3B 3C 2A 2A 3A 3B 3C 3A 3B 3C<br>2000 2003 2006 9th 2006 10th 2006 11th<br>800<br>600<br>400<br>plausible value in reading<br>200<br><!-- End of picture text --> An interesting comparison is between PISA 2000 results and the PISA 2006 additional “national option” sample. Table 7 gives estimates of the relative difference between achievement of students in vocational and other tracks in 2000 and in 2006 separately for the 10<sup>th</sup> and 11<sup>th</sup> grades. The results are striking. While the overall mean performance of Polish students improved significantly, the difference between students in vocational and other tracks remained almost the same, and even increased for 17-year-olds. Thus, the stratification of Polish students in the old secondary school system still exists under the new name of upper secondary schools. It seems that the reform helped to update the skills of the average student, but the negative effect of the tracking system was simply postponed by one year. The achievement gap noted in PISA 2000 is still visible and almost of the same magnitude. From one point of view this is not surprising, since the reform focused on primary and lower secondary education. On the other hand, it is now evident that the overall effect of the reform is not so positive. Intuitive claims that upper secondary education did not improve that much seems to be supported by the results presented here. Clearly, while there are visible positive effects of the reform, there are also doubts whether these positive effects are long lasting or affect all students similarly. Still, students in vocational tracks lack knowledge and skills needed to fully benefit from the modern society and economy and the reform did not change that.

23
Given this, it is perhaps surprising that over one in five VFs _do_ borrow to on-lend. The inherent reluctance may perhaps be overcome by ambitious local leadership, or a particularly strong (unmet) demand for credit – for instance, in large villages, or villages with low loan penetration by the BAAC. We would expect onlending to be more common when the VF sets its lending rate high enough to cover the cost of borrowing from the BAAC or GSB, and we anticipate that honoraria to VF members will be larger when the committee takes on risk.

Lending is inherently risky, given that borrowers may not want, or be able, to repay. Indeed one might ask why a VF, if it is indeed altruistic, asks borrowers to repay: why not simply give away the windfall funds once and for all, and save itself the trouble of managing the rotating credit year after year?

One possibility is that other central government benefits that flow to a village may be, or be seen to be, linked to how well the VF is managed. In 2003 and 2004 some VFs were provided with modest additional working capital – typically about 100,000 baht – if they were well-run. The Yingluck administration elected in July 2011 has promised to provide an additional million baht per village; if this only goes to VFs that continue to operate, then VF insistence on loan repayment will have borne fruit.

The distinction between on-lenders and other VFs matters, as Table 12 makes clear. VFs that borrow to onlend are able to lend more, have higher profit and loan recover rates, have better credit ratings, and lend relatively more to the poor.

**<mark>Table 12.  Performance Measures, by On-Lending Status</mark>**

||Does Village Fund<br>|Borrow to On-lend?<br>|
|---|---|---|
|**Performance measures**|No|Yes|
|Loan recovery rate, %|70.3|84.6|
|Capital available, millions of baht per fund|1.273|2.597|
|Lending, millions of baht per fund|1.103|1.970|
|Profit rate, %|-18.0|0.4|
|Adults borrowing from VF, %|10.4|13.1|
|Social contributions,thousands of baht|6.25|6.85|
|**Credit rating (totals to 100%)**|||
|None/Not known, %|36|17|
|A, %|5|3|
|AA, %|30|36|
|AAA,%|29|44|
|Loans topoor/loans to non-poor(rural areas only)|1.61|1.82|
|Source: Village Fund Survey 2010, and 2009 SES (for fin|al row).||

In an attempt to understand better the phenomenon of VF borrowing to on-lend, we used the data from the 2010 VF survey to estimate a logit model where the dependent variable is set to 1 if the VF borrows to on21
**Policy, Research, anJ External Atfairs**

**Trade Pclicy** WPS 426

T hisppaper a- product of ltleTralde Polic) Di ision Counltr EconomicsDepartnmct-ispartofalarger effort in **PRE** to analyze **thc** sustainabilitv **oi** structural adjustie **nt** programs. The **paper** is part of **thc** research project orn trade refonrm in structural adjustment loans (RPPG 675-32). Copies are available free from the World **Bank,** I81 Ili Strcet NW, Washington DC 2(033. Please contact Maria Ameal, room NI(031, extension 37947 (33 pages '. ith tahbes).

What happened to cconiomic perrirmanic in developing countrics under oro( ih-oricniitd adjustmcnt programs sponsored i' tteC World Bank and thte INiF?

Analyzinjg data for a sample of 93 CoLuntriC S. Fai li, de M(elo, Senhadji-SelLikii, and St anton compared **the** average values of cconomic indicators for 1982-86 with the corrcspondinei values lr 1978-8 1. They control lcidlor the external environment and initial condition:%, antd **al** loA ced or policies l that ould 1 % _c_ ha n idopldt iI _tlie CoultllieoS_ hIci Iated in aidjUstlimCeIt.

**Thic** toutilld o tati **cal** cx idenee tdeniit. l (or slok er) **e,rox** t lih ? _1_ t _C_ n t r1 I t I hi a I I rIei **'ri,** d loans.

1Thc found that a higher current account surplus and loAer inflation during 1978-81 were associ;itcd ~ ith bcttcr investmcnt pertormancc d uring 19S2-S6. And that deterioration in the external environment in 1982-86 was associated ith lo er gro lh during thiat period.

Thic) also cxa;mincd the investmnclt-output relationship lor 14 countries that received sizable Lrow th-ori.rintedi adjustment loans -- estimatlingi the g-.ro( ii **10rConie** because **of lo,** r a-t regate v c,tment i u ndier adjustmenl IlhC\ CoiK I Iiu' **l;tat** Sieil5 Oi SuStai nlble ICC~\ I ! t h ron eh hi h r **invcstientw Acre uno,** at **Iax it** throu ieh 19S6. 3ut **Ltlhese** results nt 'urprisi: ht ecausc considerable timeic nI ,1 a 1', iol or the b **nefits** of structural **relfonn** to n at c n ll **l/** e Fh,k 'RI. Woiirking P'.q;><r A<1>x,>'!,I.i' i". _, .! Uq Ti ilt; i **C** i T 11 1 !!1; **lIx** i < %'i I R **car** 8;u , wi.d F _.. i_ c rTl **.i** **_A_** _tI_ lr ( .1ic:< x A i **k** 5 > i, ,i 1 ti i T i 1 i < - t ci t1 irl,.!!g _C"I_ Ce.tKi+' _11_ it **I)TOICrIIA11011S** _.u._ **11!SS t11.u** fUli'L ;all}i >l :4? lDi lil,El. r;.llel ul: iil : . > s+ !.> i'!;''''i :II 1:''''1! 1r.1i Bankl.s **.lIN .1a''**
7 2006) use a panel of professional educators to assess the minimum spending necessary to deliver instructional programs for schools of varying size and demographic composition and conclude that California‟s schools underspend. They conclude that only 15 to 28 of the 984 school districts examined were spending at the level adequate to reach California‟s content and performance standards in all major subjects. The authors estimated that an additional $24.14 to $32.01 billion would have been necessary in the 2004/2005 school year to ensure the opportunity of all students to reach the state‟s content and performance standards. This approach begs the question of why some school districts appear to achieve much better results with similar levels of spending per pupil, and why some spend considerably more than other and yet achieve no better results.

We sourced school districts‟ educational outcomes and expenditure data from the California Department of Education‟s website.<sup>5</sup> Each year, the California Department of Education collects and reports information about student test scores in California Standards Tests (CST), current expense of education, enrolment, number of dropouts, number of graduates, and enrolment of English learners of roughly 980 local educational agencies (LEA) or school districts in California. For the purpose of our analysis, we focus on 313 of the school districts that control both elementary and high school levels (i.e., unified school districts) within its boundary and have data on CST scaled scores for math and reading in grade 5 and grade 7, current expenditures, enrolment, and poverty estimates consistently available between 2003/2004 and 2008/2009 academic years.<sup>6</sup> Californian students attending grade 2 to grade 11 take the CST in mathematics, reading, science, history, social science, and so on. Some students with disabilities take the California Alternative Performance Assessment (CAPA) and their test scores are excluded from our sample. However, students in grade 8 and beyond tend to take different CST depending on their course selection in school. We chose to focus on math and reading achievement in grade 5 and grade 7, so we have a manageable number of test outcomes that correspond to elementary school level and secondary school level.

# **International education systems—PISA**

Much has been written about the international variation in knowledge and skills emerging from exercises such as the OECD‟s Program for International Student Assessment (PISA) that

> 5 The website is <u>http://www.cde.ca.gov. The current expenditure data are adjusted to June 2000 dollar values based on the</u> Consumer Price Index (CPI) available at the Bureau of Labor Statistics website ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt. 6 14 of these school districts have some test score or enrollment data missing in some years because of their relatively small size.
**<u>Appendix table 5: Impact of Sharecropping on Input Intensity per Hectare</u>**

||**Ho**<br>|**usehold Fixed Effec**<br>|**ts**<br>|**RE Tobit (Marginal Effects)**<sup>**a**</sup><br>|
|---|---|---|---|---|
||**Male adult labor**<br>**days per ha (log)**|**Total labor days**<br>**per ha (log)**|**Pair of oxen**<br>**days per ha (log)**|**Quantity of fertilizer in**<br>**Kg/Ha**|
|Sharecrop dummy|-0.150***|-0.156***|-0.194***|-0.283***|
||(-4.870)|(-4.990)|(-6.382)|(-4.448)|
|Fixed rental dummy|0.011|-0.017|-0.032|-0.143|
||(0.142)|(-0.218)|(-0.414)|(-0.948)|
|Number of years possessed|-0.002|-0.002|-0.004**|-0.008**|
||(-1.220)|(-1.400)|(-2.170)|(-2.193)|
|Good soil quality|0.107***|0.147***|0.117***|-0.055|
||(3.270)|(4.429)|(3.624)|(-0.829)|
|Medium soil quality|0.073**|0.097***|0.062**|0.071|
||(2.288)|(2.985)|(1.979)|(1.108)|
|Flat land|0.065|0.068|0.009|-0.102|
||(1.281)|(1.313)|(0.189)|(-0.998)|
|Gently sloped land|0.068|0.071|0.034|-0.236**|
||(1.269)|(1.294)|(0.647)|(-2.174)|
|Irrigated land|0.101*|0.120**|0.155***|-0.210|
||(1.755)|(2.057)|(2.736)|(-1.615)|
|Teff|0.442***|0.530***|0.356***|2.503***|
||(9.606)|(11.313)|(7.830)|(18.301)|
|Wheat|0.337***|0.382***|0.343***|2.573***|
||(7.157)|(7.969)|(7.370)|(18.471)|
|Sorghum|0.126***|0.234***|0.140***|0.962***|
||(2.692)|(4.878)|(3.023)|(7.518)|
|Pulses|-0.113**|-0.109**|-0.094*|0.290*|
||(-2.204)|(-2.084)|(-1.861)|(1.934)|
|Constant|3.895***|4.219***|2.634***||
||(53.077)|(56.391)|(36.320)||
|Number of observations|5443|5443|5443|5443|
|Number of households|826|826|826|826|
|_R_<sup>2</sup>|0.095|0.111|0.077||
|Log-Likelihood||||-15041.72|
|Chi-squared||||1443.746|

**Note:** Absolute value of t statistics in parentheses; * significant at 10%; ** significant at 5%; *** significant at 1%. a The reported marginal effects for the fertilizer regression are provided in the form of dlny/dx such that we can interpret the coefficient of the tenancy dummy similarly to that of the labor and draft power intensity regressions as the percentage deviations of input intensities on sharecropped plots relative to owner-cultivated plots.

30
**_Correction for inflation._** Egypt has experienced rapid inflation between 2005 and 2008.  It is therefore important to rely on real values for comparisons over time.   The CPI index disaggregated by regions and into food and non-food component was used. The second way was to use the poverty lines for each household re-estimated in actual prices as deflators (consumption is then measured in terms of poverty baskets a household can purchase in the current month, see El Laithy and Lokshin, 2003, for methodology).

# **IV. Economic growth, inequality and poverty over 2005-08: A cross-sectional perspective**

Egypt witnessed rapid and sustained economic growth during 2005-08. This episode followed a period of economic turmoil (large depreciation of national currency) and slow, at times almost zero, growth in per capita consumption. In contrast, real GDP annual growth averaged over 6 percent, leading to an accelerated growth in total final household consumption expenditure. In per capita terms, private consumption grew at an average rate of almost 4 percent per year in this period. The HIECPS data for 2005-2008 shows remarkably similar picture. Households' real average per capita consumption<sup>14</sup> increased by 12.3 percent between 2005 and 2008 (3.9 percent per year) – practically identical to macroeconomic estimates from the National Accounts (Table 1). But price increases for goods and services consumed by households were also staggering. Inflation over the period was very uneven: prices of food and other basic goods and services increased much faster than other prices. The cost of the subsistence minimum food basket increased by 47 percent, far more than the overall increase in the CPI (31 percent over the three years).

**Table 1: Survey Results – Growth in Monthly Mean Consumption**

|||**Consumption per**|**capita in 2005 LE**||
|---|---|---|---|---|
||**February 2005**|**February 2008**|**Growth 2008-**<br>**2005 (percent)**|**Annual growth**<br>**rate (percent)**|
|Urban|3,007|3,430|14.1|4.5|
|Rural|1,868|2,057|10.1|3.3|
|**Total Egypt**|**2,352**|**2,641**|**12.3**|**3.9**|

_Source: Authors estimates based on HIECPS 2005-2008 and regional CPI indices. Note: Table uses actual_ _household size to weight data._

> 14 Using CPI index to deflate nominal figures.

9
Policy Research Working Paper 8548

# **Abstract**

Rural access is among the most important infrastructure constraints in rural Africa. Using the results from comprehensive household surveys and other data from Ethiopia, the paper recasts light on the heterogeneous impacts of road accessibility on agriculture and nonagricultural growth. It is found that crop production is increased by major and feeder road improvements. Significant synergy is also found. When investigating further into this effect, there are two impacts: farmers’ access to the input market, especially fertilizer, was improved mainly by major corridor improvement. And output market access was improved by feeder road improvement. In addition, the household’s nonagricultural income is somehow increased by improved road connectivity. There must be secondary effects. The transport demand function estimated with additional data indicates that as the road network improves, people’s mobility increases. Furthermore, local business employment is found to increase with road improvements. To meet the increasing demand for mobility, efficiency and frequency of transport services are important.

This paper is a product of the Transport and Digital Development Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at aiimi@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
|Time Tax (Country level average)|Country-level average of the percentage of<br>firms’ senior management’s time that is spent<br>in dealing with business regulations.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|---|---|
|Population (lagged, logs)|Total population in the country. Values of the<br>variable used are one year prior (that is, lagged<br>by 1 year) to the fiscal year covered by the ES.<br>In cases where the fiscal year covered by the<br>ES spans more than one calendar year, the<br>population figure is the weighted average over<br>the calendar years covered (lagged by 1 year),<br>where the weights used are the proportion of<br>firms covered by the ES in the calendar year<br>(lagged by one year).<br>Source: World Development Indicators,<br>World Bank.|
|Rule of Law (lagged)|Rule of Law indicator from Worldwide<br>Governance Indicators. Higher values of the<br>variable imply better enforcement of rules and<br>laws. The variable is lagged by 2 years from<br>the fiscal year covered by the Enterprise<br>Survey in the country. In cases where the fiscal<br>year spanned more than one calendar year, the<br>Rule of Law figure is the weighted average<br>over the calendar years covered (lagged by 2<br>years), where the weights used are the<br>proportion of firms covered in the calendar<br>year.<br>Source: Worldwide Governance Indicators,<br>World Bank.|
|Freedom From Regulation (lagged)|Freedom from Regulation indicator from<br>Fraser Institute’s Economic Freedom of the<br>World database. Higher values of the variable<br>imply less regulation (of formal businesses).<br>The variable is lagged by 2 years from the<br>fiscal year covered by the Enterprise Survey in<br>the country. In cases where the fiscal year<br>spanned more than one calendar year, the<br>figure used is the weighted average over the<br>calendar years covered (and lagged by 2<br>years), where the weights used are the<br>proportion of firms covered in the calendar<br>year.<br>Source: Economic Freedom of the World,<br>Fraser Institute.|

41