rafmacalaba/datause-encoder-data huggingface dataset:
balancing can be traced back over half a century to Richard Stone and his colleagues (1942) when they explored procedures for compiling national income accounts. Their ideas were formalized into a mathematical procedure to balance the system of accounts after assigning reliability weights to each entry in the system. The minimization of the sum of squares of the adjustments between initial entries and balanced entries in the system, weighted by the reliabilities or the reciprocal of the variances of the entries is carried out subject to linear (accounting) constraints. This approach had first been operationlized by Byron (1978) and applied to the System of National Accounts of the United Kingdom by van der Ploeg (1982, 1984). Zenios and his collaborators (1989) further extend this approach to balance a large social accounting matrix in a nonlinear network-programming framework. Robinson and his colleagues (2001) provide a way to handle measurement error in cross entropy minimization via an error-in-variables formulation. Although computational burden is no longer a problem today, the difficulty of estimating the error variances in a large data set by such approaches still remains unsolved.

The objectives of this paper are threefold. The firstis to develop and implement a formal model to estimate interregional, interindustry transaction flows in a national system of economic regions based on incomplete statistical information at the regional level. The second is to evaluate the model’s performance against data from the real world. And the third is to discuss the issues that arise when applying this modeling framework to estimate a multi-regional input-output account containing well-defined sub-regions.

The paper is organized as follows. Section 2 specifies the modeling framework and discusses its theoretical and empirical properties. Section 3 tests the model by using a four-region, ten-sector data set compiled from a global database documented in McDougall, Elbehri, and Trong (1998). Test results from seven experiments are evaluated against eight mean absolute percentage error indexes. Section 4 discusses some empirical issues involved in applying such a framework to data from a national statistical system. The paper ends with conclusions and direction for future research.

6
data and do not control for the possible endogeneity of the input use or the selection of high yielding variety (HYV) seeds.

In this paper, we follow the approach taken by Marenya and Barrett (2007) but use two-year panel data of farm households in Kenya and Uganda where we have maize production data on 6,329 plots, of which we have soil fertility data for more than 70 percent of the plots. Kenya and Uganda provide an interesting comparison because Kenya has one of the highest productivities for maize in Africa, while Uganda has one of the lowest (Smale and Jayne, 2003; Sserunkuuma, 2005). We control for the HYV selection by using the household fixed effects semiparametric endogenous switching model, developed by Kyriazidou (1997). In particular, we estimate the direct impact of the soil fertility on the maize yield and examine if the soil fertility increases the returns to inorganic and organic fertilizer. The results of the analyses indicate that the Kenyan maize farmers have applied the inorganic fertilizer roughly at the optimal level in one out of the two survey years on both the purchased HYV and local/recycled HYV maize.<sup>2</sup> In Uganda, even the low application of inorganic fertilizer is not profitable because of the high relative price. Regarding the returns to external fertilizers on degraded soils, we do not find any increasing marginal returns of external fertilizers to the soil fertility.

The paper is organized as follows. Section 2 explains the production model that captures the interactions between the soil fertility and the fertilizer inputs and describes the semi-parametric endogenous switching model used in this paper. Section 3 explains the household panel data and soil fertility data. The surveys in both countries were conducted by the same research project which employs comparable questionnaires

> 2 Many farmers in Kenya and Uganda recycle purchased HYV maize after harvesting. We group the recycled HYV maize with the local maize as we explain later in Section 2.

3
24 Koropeckyj, I.S. and G.E. Shroeder, Economics o Soviet Regions (Praeger 1981). Kuznets, Simon, Modern Economic Growth Rate Structure and Spread<sup>(New Haven:</sup> Yale University Press, 1966).

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OECD, Services in Central and Eastern European Countries (Paris, 1991). Millar, James, Politics. Uork. and Dailv Life in the USSR: A Survey of Former Soviet Citizens (Cambridge & New York: Cambridge University Press,<sup>1987).</sup> Ofer, Gur, The Service Sector in Soviet Economic Growth: A Comoarative<sup>Study</sup> (Cambridge: Mass: Harvard University Press, 1973).

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Page 3 grants to schools so that they can decide on their own spending priorities. A pilot School Improvement Grant (SIG) scheme is being considered by MoES to give greater responsibility directly to school stakeholders for decisions over resources.

**Figure 2. Service Delivery and Accountability Relationships in Albania’s Pre University Education Sector**<sup>**4**</sup>

<!-- Start of picture text --> Government<br>MoES<br>RED<br>employs<br>holds accountable<br>School director<br>and teachers<br>provides<br>School services<br>board to<br>Parents<br><!-- End of picture text --> Source: Serra, Barr and Packard (2011) 9. A key objective of the _Accountability for Better Governance_ analytical program, initiated in the summer of 2008, is to measure household perceptions and experiences of governance in the education sector, and given this experience, their demand for accountability. Although planned improvements to education governance are ongoing, the analytical program provides important feedback to the government –in the form of responses to new household and facility user surveyson its efforts thus far. Additionally, since further measures to improve the performance of school governance structures as well as to increase school autonomy are still being considered, the program offers an opportunity to rigorously and scientifically explore the impact of reforms piloted as part of the _Albania Education Excellence and Equity Project (EEE-P)_ . Towards this end, the program provides a baseline of data on the performance and functioning of pre-university primary schools that was not previously available to the government. Strengthening accountability mechanisms in order to improve governance is one of the core development objectives of the _EEEP_ , supported with co-financing from the government, the World Bank, the European Investment

> 4 The figure simplifies the existing accountability relationships in two ways, although all the essential elements are represented.  First, the figure does not show local governments that are also subject to elections, but who have no power over REDs.  Second, according to MoES guidelines, a the community level parent members of the School Boards should be elected parent class representatives, The parent class representatives of each grade are together members of the school‟s Parent School Council.  Members of this Council elect from among themselves parent members of the School Board. Thus a necessary condition for the School Board to function as intended, is that its parent members are elected by elected parent class representatives, who themselves are chosen by parents participating in the accountability process.
14 Table 4: Ukraine Evolution of the Official and Unofficial Economy (unitary elasticity scenario)

||1989|199Q|1291|192|199|1994|
|---|---|---|---|---|---|---|
|Official Economy Index|88.0|84.7|73.3|60.5|_51.5_|38.9|
|Unofficial Economy Index|12.Q|16.3|25.5|32.2|_34.0Q_|_M_|
|Overall Economy Index|100.0|100.0|98.8|92.7|85.4|75.4|

On the basis of the index numbers in Table 3, which show the extent of the decline of the economy in Ukraine, it is also easy to calculate the relative shares of the official and unofficial economies, as shown in Table 5.

Table 5: Ukraine Relative Shares of Official and Unofficial GDP (unitary elasticity scenario)

||12M2|199|1991|1992|1993|1994|
|---|---|---|---|---|---|---|
|Official Economy Share|88.0|83.8|74.2|65.3|60.3|_51.5_|
|Unofficial Economy Share|12.0|16.2|25.8|_347_|397|48.5|
|Overall Economy Share|100.0|100.0|100.0|100.0|100.0|100.0|

Following the same approach for the other two more conservative scenarios, we can calculate the unofficial economy index and shares, respectively, and present all three scenarios together in Tables 6 and 7. The data of Table 7 is depicted graphically in Figure 2.

Table 6: Ukraing Unofficial Economy Index: three scenarios.

|||Uno|fficial Ec|onomy_I_|_ndex_||
|---|---|---|---|---|---|---|
||1989|1299|1991|1292|1993|1994|
|Unitary Elasticity Scenario|12.0|16.3|25.5|32.2|34.0|36.6|
|Conservative Elasticity Scenario|12.0|16.5|25.2|30.9|31.5|32.7|
|Overall Conservative Scenario|12.0|14.8|22.5|28.0|28.8|30.9|
Burtraw, Dallas, Alan J. Krupnick, Erin Mansur, David Austin and Deirdre Farrell, 1998. “The Costs and Benefits of Reducing Air Pollutants Related to Acid Rain.” _Contemporary Economic Policy_ 16: 379-400.

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> DfT, 2004. _Feasibility Study of Road Pricing in the UK—Report_ . United Kingdom Department for Transport, London.

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Eskeland, Gunnar S. and Feyzioglu, Tarhan, 1995. “Rationing Can Backfire: The ‘Day Without a Car’ in Mexico.” World Bank Policy Research Working Paper 1554.

Eskeland, Gunnar S. and Torben K. Mideksa, 2008. “Transportation Fuel Use, Technology and Standards: The Role of Credibility and Expectations.” Policy Research Working Paper 4695, World Bank, Washington, DC.

Eskeland, Gunnar S. and Feyzioglu, Tarhan N. & DEC, 1994. “Is Demand for Polluting Goods Manageable? An Econometric Study of Car Ownership and Use in Mexico.” Policy Research Working Paper Series 1309, The World Bank.

> FHWA, 2000. _Addendum to the 1997 Federal Highway Cost Allocation Study Final Report_ . US Federal Highway Administration, Department of Transportation, Washington, DC.

Glaister, Stephen and Dan Graham. 2002. “The Demand for Automobile Fuel: A Survey of Elasticities.” _Journal of Transport Economics and Policy_ 36: 1-25.

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and created a foundation for family-based farming. Since then, China has sustained its output growth, largely benefiting from growing agricultural Research and Development (R&D) investment and high use of key inputs such as fertilizer and irrigation systems.<sup>2</sup> However, in recent years, China’s demand for food appears to have been growing more quickly than its supply. As a result, China’s trade position for food has turned from surplus to deficit, and this gap has been widening (Fukase and Martin, forthcoming). Some concerns about China’s food self-sufficiency have arisen among Chinese policy makers and other stakeholders, especially since China is relatively poorly endowed with agricultural land and water supplies compared to its population base.<sup>3</sup> A World Bank project on urbanization and food security has recently devoted a great deal of research to the question of China’s food demand and supply. This research looks in detail at key issues such as the impact of urbanization on China’s food self-sufficiency and food security (Huang et al., 2013), on land availability (Deng, Huang and Rozelle, 2013) and on water availability (Wang, Huang and Rozelle, 2013). Using detailed structural models built up from estimated parameters of demand systems and production structures for China, Huang et al.’s study (2013) predicts that China will need to import feed grains and some other foods for some time but that its overall food self-sufficiency is likely to remain at above 90 percent level through 2030. Their results are consistent with those obtained from other studies, for instance, the forecast for China by 2022 prepared by OECD/FAO (2013) and a recent study using a multicountry multi-sector applied general equilibrium model (Anderson and Strutt, 2013).<sup>4</sup>

> 2 Since the economic reforms, China has sustained an impressive annual growth rate in agricultural total factor productivity (TFP) of over 2 percent (Huang et al., 2013).

> 3 China has about 20 percent of the world’s population and 35 percent of its agricultural labor force, but has only 11 percent of the world’s agricultural land and less than 6 percent of its water resources (Christiaensen, 2012).

> 4 Using the Global Trade Analysis Project (GTAP) model, Anderson and Strutt (2013) project that China’s agricultural self-sufficiency rate may fall about ten percentage points from the baseline level of 97 percent by 2030.

3
Development Economics Education.<sup>9</sup> Regional economics associations could potentially play a role in helping instructors share learning materials.

# **References**

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Bardhan, Pranab (2013), “Little, Big: Two Ideas about Fighting Global Poverty”, _Boston Review_ , May 20.

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Kanbur, Ravi (2005), _“_ Goldilocks Development Economics: (Not Too Theoretical, Not Too Empirical, But Watch Out for the Bears!)”, in Ravi Kanbur, ed., “New Directions in Development Economics: Theory or Empirics?” a symposium in _Economic and Political Weekly_ , typescript, August 2005.

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> 9 http://www.ufrgs.br/redesenv/programas.

22
2009. Venezuela is excluded because the country underwent a currency regime change and there are doubts if sales figures were reported in the old or new currency. The sample is slightly reduced to 11,368 firms after restricting to cells with at least thirty bribery responses.

Seventy-four percent of the full sample (9,104 firms) conducted at least one of the six business transactions, and recall that a firm must participate in at least one transaction to have bribery data. Panama has the lowest proportion of firms who conducted at least one business transaction (40 percent). The coverage in the remaining countries is quite high, at least half, and over 90 percent of firms in Guyana conducted at least one business transaction. Historical data on past annual sales has a lower response rate than other variables used in the analysis. These two factors and excluding firms with other missing information reduce the sample to 6,554 firms, which is referred as the regression sample.

There is very little difference in the statistics on explanatory characteristics across sample restrictions. For example, in both the full and regression samples, 16-17 percent of firms are exporters. About 30 percent of firms use external financing for investments, 26 percent of firms are sole proprietors, and 15 percent of firms have at least 10 percent foreign ownership. The average age of firms in the region is 18 years. The distribution of firms across industries is also similar between the full and regression samples.

In the full sample of LAC firms, a total of 17,513 reported business transactions were reported, and 1,052 transactions (6 percent) included a bribe solicitation that affected 981 firms. Among firms conducting business transactions, average annual sales growth is higher for firms who were never bribed than for firms who were bribed (3.3% vs. 0.3%). In the regression sample, the difference in sales growth for bribed or non-bribed firms is virtually is identical to the full sample. It is important that firms are not systematically excluded from the sample based on their characteristics.

Real annualized sales growth is higher in the regression sample, but insignificantly so by less than half a percentage point. Controlling for characteristics in the previous period is important when estimating growth. In 2007, the average firm had 32 full time employees and an average worker produced $43,914 USD.

10
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