rafmacalaba/datause-encoder-data huggingface dataset:
|Age=12|(0.1524)**<br>-0.3023|(0.1600)**<br>-0.35|(0.1625)**<br>-0.3653|(0.1773)**<br>-0.3586|
|---|---|---|---|---|
||(0.1657)|(0.1683)*|(0.1672)*|(0.1854)|
|**_Pre-programme share of childr_**<br>|<br>**_en in the popula_**|<br>**_tion in region of_**<br>|<br>**_birth x birth coh_**<br>|<br>**_ort_**<sup>**_(a)_**</sup><br>|
|Cohort 1: 1-6yrs in 1974||-5.9802<br>(5.6076)|-14.3012<br>(5.4523)**|-15.1135<br>(5.6417)**|
|Cohort 2: 7-12 yrs in 1974||-12.0803<br>(6.2204)|-21.5738<br>(6.0806)**|-22.8432<br>(6.3838)**|
|**_Pre-programme enrollment rat_**|**_e in region of bi_**|**_rth x birth cohor_**|**_t_**<sup>**_(a)_**</sup>||
|Cohort 1: 1-6yrs in 1974|||18.287<br>(1.8483)**|18.3632<br>(1.8411)**|
|Cohort 2: 7-12 yrs in 1974|||20.0913<br>(2.4157)**|20.0457<br>(2.3670)**|
|**_Allocation of water and sanitat_**|**_ion programmes_**|**_in region of birt_**|**_h x birth cohort_**<sup>**_(a)_**</sup>||
|Cohort 1: 1-6yrs in 1974||||-0.0863<br>(0.6884)|
|Cohort 2: 7-12 yrs in 1974||||0.0444<br>(0.8727)|
|Constant|4.5886<br>(0.2287)**|4.5317<br>(0.2307)**|4.2357<br>(0.2406)**|4.2181<br>(0.2414)**|
|Observations|5,875|5,820|5,788|5,439|
|R-squared<br>|0.13|0.13|0.17|0.15|
|Ftest: interactions=0<sup>(b)</sup>|7.43|7.40|6.71|6.32|
|Prob>F|0.0000|0.0000|0.0000|0.0000|

Notes (a) The control group was women aged 13-24 in 1974 (b) F-test to test the hypothesis that interaction coefficients between cohort of birth and programme intensity in the region of birth are jointly zero Robust standard errors in parentheses

* significant at 5%; ** significant at 1%

38
lengthened several time to fifty years). In 1981 the central government approved the implementation of HRS nationwide and by 1984, 99 percent of rural households participated in HR.S. Rural reforms were successful with growth in agricultural yields accelerated, and rural income rose rapidly.

Rural industry developed rapidly as rural reforms created several favorable conditions. First, income rose and more savings could be invested in rural industries which have higher rate of returns than farming. Second, reforms boosted productivity and freed surplus labor and provided a steady supply of workers for rural industries. Government provided support to rural industries since 1984 in the forms of easing state control on materials, allowing sub-contracting by urban finns, and low taxation to township and village enterprises (TVEs). The share of collectively owned enterprises grew rapidly: in 1978 these enterprises accounted for 22 percent of industrial output. This share rose to 30 percent in 1984 and to 36 percent in 1988, where it has remained since.

China opened its doors to foreign trade and investment steadily at an early stage of reforns. First China reformed its trading system by increasing the numbers of firms allowed to trade internationally, by lowering tariffs on imports steadily and giving exemptions. Second, initially exporters were allowed to retain a portion of foreign exchange receipts. Government maintained a realistic exchange rate policy and devalued five times since the reform started. Interbank market for foreign exchange was developed and the dual exchange rates were unified at the market rate in 1994. Third, regulations on foreign direct investment were gradually relaxed. Four special economic zones (SEZs) were established in 1980. and a fifth was added later, which offered foreign investors special fiscal, infrastructural and financial incentives. By 1993, more than 9,000 economic zones were established throughout China, which played important roles in attracting foreign direct investment, stimulating trade, bringing in advanced technology and upgrading industries.

# Reforms in **public finance,** financial and enterprise sectors (1984-89)

This period was marked by partial reforms in many areas and a dual-track price/exchange rate system. The scope of planning has been gradually reduced, with the number of materials in the state unified plan decreased from 256 in 1980 to 27 in 1988. Starting in 1984, dual price approach was adopted in which the prices of products and materials allocated by the plans were set by the government, whereas the prices of the same products and materials allocated by non-planning channels were determined by the market. This approach allowed decision-making to be determined at margin by market prices, but at the same time created rampant rent-seeking behavior and corruption.

**Table A2.1**

**Share of Goods Sold at State-fixed Prices, 1978-93 (percent)**

|**Year**|Retail|Agricultural|Capital goods|
|---|---|---|---|
||commodities|goods||
|1978|97|94|100|
|1992|10|_15_|20|
|**1993**|5|10|15|

Source: Lardy 1994 37
sd), and statistically significant at the 5 percent level. As a result, both programs had a positive and statistically significant impact on learning for girls at midline. Note that boys in the control group out-perform girls by 0.18 sd on average. This means that the programs also succeed at reducing the difference in performance between boys and girls, by roughly a third and two thirds in the in-kind and recognition arms respectively.

In columns (3) and (4) we report the same results as above, but for female and male teachers separately. Again, the comparison between Columns (1) and (2) is important since it confirms that the restricted sample for which we can ascertain a teacher’s gender does not drive the results. The effect for a female teacher on female students is 0.21 sd for the in-kind treatment, and 0.24 sd for the recognition treatment; with both being statistically significantly different from zero at conventional levels. The effects of a female teacher on male students is very similar: the interactions between treatment arm and the boy indicator are small and non-significant. In contrast, there are differential effects for male teachers (Column 4). In this case, the effect for a male teacher on a female student in the in-kind treatment is 0.27 sd, while the effect on male students is 0.12 (0.27-0.15) sd; we note that the coefficient on the interaction term, -0.15, is not statistically significant. The effect for a male teacher on a female student from the recognition treatment is 0.13, which is not statistically significant different from zero, and the effect on male student is -0.08 (0.13-0.21) sd which is negative but not statistically significantly different from zero.

In sum, these estimates present an intriguing perspective of the effects of teacher incentive programs. On one hand, there is supporting evidence that female teachers respond to both pecuniary and non-pecuniary incentives, and do so in ways that benefit all students, male and female. On the other hand, the estimates indicate that male teachers respond mainly to the pecuniary incentive, and do so in a way that benefits only female students. This behavior is compatible with them taking a strategic approach, since female students of male teachers tend to have markedly lower counterfactual test scores than male students.

# **3.3 Inspectors’ Classroom Observations**

We further investigate the ways through which teachers may have responded to incentives by using the data on teacher practices collected through the inspector classroom observations. The inspector assigned each teacher scores on two indicators of classroom quality and five indicators of teaching quality. We standardized each score to have a control group mean of zero and standard deviation of one, and then took the mean of these standardized scores to create an overall index of classroom and teaching quality, respectively. Table 4 reports the effects of the program on these indicators at midline. The specification is similar to that for 12
- 40 -

# **REFERENCE**

- Auriol, Emmanuelle. 2006. Corruption in procurement and public purchase. _International Journal of Industrial Organization_ , Vol. 24, pp. 867-885.

- Bajari, Patrick, Robert McMillan, Steven Tadelis. forthcoming. Auctions versus negotiations in procurement: an empirical analysis, _Journal of Law, Economics and Organization_ .

- Bloom, David, David Canning, Jaypee Sevilla. 2003. Geography and poverty traps. _Journal of Economic Growth_ , Vol. 8, pp. 355-378.

- Boehm, Frédéric, Juanita Olaya. 2006. Corruption in public contracting auctions: the role of transparency in bidding processes. _Annals of Public and Cooperative Economics_ , Vol. 77, pp. 431-452.

- Brannman, Eric, Douglass Klein, Leonard Weiss. 1987. The price effect of increased competition in auction markets. _The Review of Economics and Statistics_ , Vol. 69, pp. 24-32.

- Bresnahan, Timothy, Peter Reiss. 1991. Entry and competition in concentrated markets. _Journal of Political Economy_ , Vol. 99, pp. 977-1009.

- Burnside, Craig, David Dollar. 2000. Aid, policies, and growth. _The American Economic Review_ , Vol. 90, pp. 847-868.

- Burnside, Craig, David Dollar. 2004. Aid, policies, and growth: reply. _The American Economic Review_ , vol. 94, pp. 781-784.

- Calderón, César, Luis Servén. 2004. The effects of infrastructure development on growth and income distribution. Policy Research Working Paper No. 3400, the World Bank.

- Canning, David, Peter Pedroni. 1999. Infrastructure and long run economic growth. Center for Analytical Economics Working Paper No. 99-09, Cornell University.

- Che, Yeon-Koo, Jinwoo Kim. 2006. Optimal collusion-proof auctions. Department of Economics Discussion Paper Series 0708-05, Columbia University.

- Easterly, William. 2003. Can foreign aid buy growth? _Journal of Economic Perspectives_ , Vol. 17, pp. 23-48.

- Easterly, William, Ross Levine, David Roodman. 2004. Aid, policies, and growth: comment. _The American Economic Review_ , Vol. 94, pp. 774–780.

- Fay, Marianne, Tito Yepes. 2003. Investing in infrastructure: what is needed from 2000 to 2010? Policy Research Working Paper No. 3102, The World Bank.

- Foster, Vivien. 2005. Ten years of water service reforms in Latin America: toward an AngloFrench model. Water Supply and Sanitation Sector Board Discussion Paper Series No. 3, The World Bank.
companies enjoyed through their diversification in other business lines is likely to have had some local spillover effects.

It is also worth highlighting an interesting regional finding arising from the results. Both leverage indicators suggest that the financing policy of operators in Latin America was much more dramatically influenced by the Asian crisis. Indeed, while there was a small increase in Asia from 25% to 40% in the leverage rate based on market values, the major increase was observed in Latin America, which has seen its leverage rate more than double as a result from the Asian crisis. These developments are shown in Table 9.

**Table 9: Average leverage by geographical area, balanced data (%)**

||**Levera**<br>|**ge 1 – Market**<br>|**based**<br>|**Leverage**<br>|**2 – Accountin**<br>|**g based**<br>|
|---|---|---|---|---|---|---|
|**Year**|**South**<br>**America**|**Asia**|**Other**|**South**<br>**America**|**Asia**|**Other**|
|1997|20.9|25.6|-2.6|21.1|30.6|-2.7|
|1998|42.3|28.2|0.1|30.2|28.9|0.1|
|1999|37.7|34.3|5.5|33.7|36.4|3.6|
|2000|50.0|33.3|2.0|38.2|29.6|0.8|
|2001|51.8|36.3|4.7|42.5|32.5|1.4|
|2002|52.9|42.9|-12.8|51.4|29.2|-6.0|

Source: Datastream and authors’ calculations.

# **4.2 Impact of the Asian crisis on the financial structure of transport operators**

Table 10 presents the results for the balanced sample with regard to the average leverage levels in the two transport sub-sectors. The results from the balanced sample analysis are somewhat different to those based on all identified data. Namely, the leverage ratios from the balanced sample show significantly higher stability than the unbalanced sample ratios over the same time period. The availability of data for transport companies has increased considerably during the past five years and, as a result, the number of companies in the full sample almost doubled between 1997 and 2002. Therefore, the trends observed in the full sample over this period may reflect new data becoming available, rather than companies choosing to alter their capital structures. The results from the balanced sample suggest that this might indeed be the case. However, evidence from both samples suggests important information about the transport companies’ capital structure choices.

13
Tariffication--conversion of non-tariff barriers (NTBs) to bound tariffs--moves agricultural trade towards the same treatment as manufactures within the GATT. As a tirst step towards liberalization, participating countries, with the exception of those covered by "special treatment" provisions (explained below), were required to convert their non-tarif'f measures to bound tariffs. While the concept is not without pitfalls as discussed in the literature.<sup>3</sup> tariffication provides the immediate benefit of achieving transparency ot' import protection. In addition, tariffs are generally preferred over othier import barriers since tlhey are more predictable, nondiscrimiinatory and easier to bind or reduce and less susceptible to corruption. They also facilitate competition in internal markets and help ensure trade adjustments by importing countries to world market changes. Moreover, even though tariflication does not deal directly witli export policies, it could provide indirect control on export subsidies. Exporting countries providing export subsidies have to maintain impcrt barriers to avoid re-importing the goods exported. Arbitrage in tihe market implies that in general a country cannot set an export subsidy higher than the level ol't he laril' plus transport costs. Hence, tarillication l'acilitates an indirect control on **lIhe** amount of export subsidies implied by removing the non-tariff barriers to reimporfing.

But how much trade liberalization will actually be achieved 1rom the UR agreement'? Recent studies (IATRC. 1994: GATT, 1994) have provided broad evaluations ol' the final Agreement, but to date, no systematic comparison ol pre- and post-UR border protection has been made on a wide range ol' agricultural commodities and countries. Most countries, particularly in OECD, converted their NTBs into specilic tariffs, preventing an easy assessment of' protection rates. The paper estimates post-UR _ad-valoreni_ tari'f' equivalents ol' order measures based on hlie

> 2This includes quantitative import restrictions, variabie levies, minimuin import prices, discretionary import licensing, non-tariff measures maintained through state trading enterprises, voluntary export restrainits and all similar measures.

> 3See Deardorff and Stern (]984) and Baldwin (1988).

2
Alpha ( α ) has units of mmd<sup>-1</sup> and is directly related to soil water storage. Regions with higher runoff coefficients generally have higher values of alpha (i.e. boreal forests and tropical rain forests) while regions with lower runoff coefficients generally have lower values for alpha (i.e. deserts and dry forests).

Epsilon ( ε ) is unitless and defines the functional form of surface runoff, which depends on the magnitude of the precipitation event and the relative storage (see Equation 4). _Smaller_ values of epsilon represent an _increase_ in the contribution of surface runoff; therefore, smaller epsilons are generally associated with smaller soil moisture capacities and greater surface runoff (e.g. tundra and chaparral). Regions with larger baseflows and flatter runoff hydrographs generally have a higher contribution of runoff from sub-surface flow. Higher values of epsilon tend to reduce the contribution from surface runoff.

AWCmult has units of meters and, as described above (Section 2.1), is directly related to land use. The greater the rooting depth of vegetation, the higher the value of AWCmult. Higher values of AWCmult tend to reduce the contribution from surface runoff.

In the current study, observed flow data (i.e. discharge from gauging stations) were obtained from some country teams. These were supplemented with additional data obtained from the Southern Africa FRIEND database (Table 4). Initially, it was intended to calibrate the model parameters using both these datasets. However, it was decided not to do this for several reasons:

- i. The limited geographical distribution of the available flow data.

- ii. The limited time available to assess data quality.

- iii. The non-trivial nature of the required task and the considerable time it would have taken to define the cells contributing to any specific station.

- iv. The numerous complications of using flow to validate runoff data (e.g. caused by the presence of wetlands, lakes, reservoirs and the abstraction of water by people).

13
# **Figure 2**

# **Excess Savings**

Financially constrained vs. Financially unconstrained firms <!-- Start of picture text --> 10%<br>5%<br>0%<br>-5%<br>-10%<br>-15%<br>-20%<br>-25%<br>Decile 1 Decile 2 Decile 3 Decile 8 Decile 9 Decile 10<br>Average Excess Savings<br>1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011<br><!-- End of picture text --> Figure 2 shows the evolution of Excess Savings for firms facing more financial constraints (decile 8, 9, and 10) and those facing less financial constraints (decile 1, 2, and 3). Firms were separated into deciles according to the value of the Whited-Wu Index, and then the average Excess Savings was computed for each year by decile.
<!-- Start of picture text --> J<br>Yr = Bro + >, BrjXpj + €r (1)<br>j=1<br>Vr X<br>EF<br>E(€r) = E(ey) = 0<br>J<br>Yu = Buo + », BujXuj + €u (2)<br>j=1<br>J<br>E(’p) = E (* +).j=1 BejXej + :| (3)<br>J<br>= Bro + >, BrjE (Xp,)<br>j=1<br><!-- End of picture text -->
This paper generalizes Markusen’s (1983) analysis by considering i) the elimination of barriers to factor movement under _any_ protection level, and ii) a change in trade barriers under free factor movement.

I show that: a) substitution obtains under low trade barriers, b) complementarity obtains under high trade barriers, and c) a change in trade barriers from the low to the high tariff region or vice versa can result in either substitution or complementarity.

These findings have important policy implications. Policymakers are likely to select a different trade policy under factor mobility than under factor immobility, assuming that they take the impact of trade liberalization on factor movement into account. The change in trade policy would likely depend on the direction and extent of the associated change in factor movement and whether or not the authorities viewed this change as desirable. The latter would depend in part on the impact of the change in factor movement on the terms of trade.

# **References**

Lopez, Ramon and Maurice Schiff. 1998. “Migration and the Skill Composition of the Labor Force: The Impact of Trade Liberalization in LDCs.” _Canadian Journal of Economics_ 31 (2): 318-36.

Markusen, James R. 1983. “Factor Movements and Commodity Trade as Complements.” _Journal of International Economics_ . 14 (3-4): 341-356.

Markusen, James R. and L. E. O. Svensson. 1985. “Trade in goods and factors with international differences in technology.” _International Economic Review_ 26: 175-92. Mundell, Robert A. 1957. "International Trade and Factor Mobility." _American Economic Review_ 47(3): 321-335.

Wong, Kar-yiu. 1986. “Are International Trade and Factor Mobility Substitutes?” _Journal of International Economics_ 21: 25 – 43.

9
**Table 7: Regressions of Prices and Markups on Market Attributes.** Robust standard errors in parenthesis. * for _p < ._ 05, ** for _p < ._ 01, and *** for _p < ._ 001.

|VARIABLES|(1)<br>Price|(2)<br>Price|(3)<br>Price|(4)<br>Price|(5)<br>Price|(6)<br>Price|(7)<br>Price|
|---|---|---|---|---|---|---|---|
|Africa (=1)|0.373***|0.160**|0.381***|0.059|0.059|0.066|0.022|
||(0.065)|(0.066)|(0.080)|(0.072)|(0.072)|(0.074)|(0.077)|
|Cement exports of neighbor (Level)||-0.040***||-0.043***|-0.044***|-0.043***|-0.042***|
|||(0.008)||(0.008)|(0.008)|(0.007)|(0.007)|
|Price of diesel||0.391***||0.398***|0.402***|0.413***|0.412***|
|||(0.049)||(0.049)|(0.050)|(0.052)|(0.051)|
|Road density||-0.048*||-0.050**|-0.051**|-0.047*|-0.033|
|||(0.025)||(0.025)|(0.025)|(0.025)|(0.024)|
|Cement tarif|||0.503|||||
||||(0.437)|||||
|Population||||-0.060***|-0.061***|-0.062***|-0.128***|
|||||(0.015)|(0.015)|(0.016)|(0.028)|
|GDP per capita||||-0.024|-0.025|-0.021|-0.028|
|||||(0.026)|(0.026)|(0.027)|(0.027)|
|Construction share of GDP|||||0.045|0.049|0.053|
||||||(0.056)|(0.057)|(0.056)|
|Procedures to start business (Z-score)||||||0.024|0.031|
|||||||(0.029)|(0.027)|
|Concentration of urban centers (Z-score)|||||||-0.127***<br>(0.048)|
|Multimarket contact (Z-score)|||||||0.013<br>(0.026)|
|Constant|4.831***|4.940***|4.777***|6.163***|6.288***|6.297***|7.471***|
||(0.043)|(0.053)|(0.066)|(0.393)|(0.449)|(0.454)|(0.613)|
|Observations|166|166|123|166|166|166|166|
|R-squared|0.169|0.388|0.195|0.430|0.433|0.435|0.464|

42
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territory. Given the volatile nature of TFP growth and the average recorded for the 1991 – 2011 period, it is assumed that the country will not experience any meaningful TFP growth in the long‐term.

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- **Growth rate of population:** ��. The population projections have been sourced from the World Bank’s Human Development Network estimates. According to the Human Development Network, the annual population growth rate for the country will decline from present 1.2 percent to 1.0 percent by 2021 and 0.7 percent by 2030.

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- **Growth rate of working age population to population ratio:** �� **.** In addition to the population forecasts, the Human Development Network also provides projections for the working age population of men and women separately. The projections indicate that the aggregate working age population to population ratio in Bangladesh will continue to rise and reach almost 70 percent by the year 2030, a gain of 4 percentage points from the current levels.

10