rafmacalaba/datause-encoder-data huggingface dataset:
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Sanderson, Eleanor and Frank Windmeijer (2015). “A Weak‐Instrument F‐test in Linear IV Models with Multiple Endogenous Variables”. Journal of Econometrics. _In press._ Solt, F. (2009). “Standardizing the World Income Inequality Database”. Social Science Quarterly. 90(2):231–42.

Stock, James and Motohiro Yogo (2005). “Testing for Weak Instruments in Linear IV Regression”, in _Identification and Inference for Econometric Models: Essays in Honour of Thomas Rothenberg_ , edited by Donald Andres and James Stock. 80‐108. New York: Cambridge University Press.

26
-

- * regulation is interested in the issue of a stand-alone business if ownership is taken into account then, as exchange rates, interest rates and tax regimes change, the regulatory body will be effectively promoting changes in ownership to achieve the lowest cost of capital. This is an issue best left to the management of the companies;

- most regulatory systems make a range of simnplifying assumptions, especially regarding tax, which mean that this level of sophistication is never reached; and

- it is difficult to establish the tax positions of all the countries involved in the study and, as such, it is better to leave them on a consistent but uncorrected basis.

This approach does not, however, completely remove the need for trying to establish the company's gearing ratio in each business, since it would be preferable to establish an asset beta for the foreign assets of companies involved in the study. Provided that there is only one 'unknown' it should be possible, through the use of comparator gearing levels, to determine an estimate of the asset beta for the unknown business.

To illustrate the approach suggested, consider the case of Kansas City Southern Industries (KCSI), a rail business in the US. This company undertakes two main activities, rail services and financial services, with the former undertaken in the US and Mexico while the latter is only undertaken in the US. This section illustrates how an estimnate of the asset beta for the Mexican rail business could be derived. The numbers used here are illustrative. Table 2-1 sets out the data used in this example.

|**_Business_**|**_% of net_**<br>**_assets_**|Comparator|**_Comparator or actual,/37_**|**_Gearing(%l)_**|
|---|---|---|---|---|
|**Group**|1000.9|0||50.0|
|**Faclials**|**2**|**S&Fiancials**|**1.10**|**30.0**|
|**R ail**|**800**|**....**<br>...............|||
|US|Rail<br>600|~~~~~~~~~~~~<br>Transport|~<br>~<br>~~~S&P<br>0.95|70.0|
|Mexican R<br>..|20...<br>...... ...<br>0||||

____________________________ From the information above, it is possible to establish values fo r the rail and Mexican rail businesses. For example, the combined rail business will have an equity beta value determined by: _0.83R =I38G_ - _0. 2/[F_ _R=_ 0.68 0.60. 8= _0.85_ Similarly, with a proxy for the US Rail equity beta, it is then possible to determine the estimate of the Mexican Rail **_equity_** beta. Further, given the information on KCSI's capital structure and the proxy values for gearing for financial services and US rail, an asset beta can be estimated for the Mexican rail business. These results are set out in Table 2-2.

**_Comparator or Gaig(/lo)fi actual_**<sup>**_13_**</sup> **_e_**

**_Business %o of net_** Comparator **_assets_**
occurrences is 0 _._ 08 days larger for villages that are one standard deviation (about 6 km) farther away from their subforest. Apart from baseline levels of forest fires and the distance between subforests and villages, none of the other covariates are found to affect the intervention’s overall effectiveness.

# **7. Conclusions**

In this paper we evaluated the impact of a forest fire prevention program in twelve of Burkina Faso’s protected forests. Forest fires cause environmental damage in the form of both the increased emissions of greenhouse gasses and biodiversity loss. Forest fires are particularly damaging in arid regions because low precipitation results in fires spreading wider and vegetation regeneration being slower, resulting in forest fragmentation and degradation. Most of the forest fires in Burkina Faso are anthropogenic, with fire being used in economic activities such as agriculture (with the ashes acting as a natural fertilizer), cattle herding (to produce new shoots for grazing), hunting (to drive out game), or charcoal production. Reducing the frequency and size of man-made forest fires is thus essential for sustainable development, but evidence on effective fire reducing forest conservation policies is scarce.

The program we evaluate aimed to raise community awareness about the importance of preventing and mitigating forest fires, and to provide both the tools and knowledge necessary for forest fire containment. We use satellite images to monitor forest fire occurrences in each of Burkina Faso’s 77 protected forests, for the period 2004-2019. We thus observe the frequency of forest fires in the intervention forests, and we use the Synthetic Control Method Abadie et al. (2010) to estimate each treatment forest’s counterfactual outcome by assigning proper weights to each of the non-treatment forests.

We show that overall the program was not very effective in reducing forest fires. We find that the program reduced forest fires at the end of the agricultural season (in November) – after harvest, when farmers tend to use fire to burn the crop residue 30
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# _Improve Fiscal Transparency and Financial Accountability_

These are desirable reform measures but in countries with high incidences of corruption and absence of rule of law, they have proven to be less effective in improving government performance. This is because fiscal transparency initiatives in developing countries typically result in making complex and incomprehensible data available to public in a non-user friendly manner. Most citizens have neither the interest nor the ability to sift through complex morass of fiscal data that lack any service delivery performance information. Such complexity of details devoid of any performance information simply reinforces citizens’ mistrust of their governments. Strengthening financial accountability have also not yielded the desired results in improving government effectiveness in countries with poor governance as in corrupt environments they have failed to prevent cooking the books at least change citizens’ perceptions regarding such perceived malfeasance. The usual perception in developing countries is that measures to strengthen financial accountability simply allow corrupt officials to maintain consistent set of accounts without curtailing their corrupt acts (see also Khan, 2007, Dye, 2007, Shah, 2007, De Mello, Jr., 2000). Recent experiences of OECD countries suggest that such measures improve government performance, if there is good governance in the first place. Further even in OECD countries, the success of fiscal transparency initiatives depend upon: (a) simple and relevant information being provided to citizens in a user-friendly manner; (b) citizens have the opportunity to engage without being overtaxed by excessive consultation requirements; and (c) the citizens trust government’s resolve to transparency and integrity (see Wright, 2008). The above conditions are often not satisfied in transparency initiatives undertaken by governments in countries with high incidence of corruption.

# _Build Technical Capacity_

Building technical capacity is of little use in public sector environments that are ripe with rent seeking. Lack of technical capacity has little to do with dysfunctional governance in 9
<!-- Start of picture text --> Figure 1. Colombia’s Income Gini Coefficient in an International Perspective<br>(a) Colombia ranks 7 th Worldwide... (b) ...and 2 nd highest in Latin America.<br>Bolivia<br>Namibia Colombia<br>Honduras<br>Comoros<br>Brazil<br>Botswana Paraguay<br>Panama<br>Belize<br>Chile<br>Haiti Costa Rica<br>Angola Ecuador<br>Peru<br>Colombia El Salvador<br>South Africa Mexico<br>Dom. Rep.<br>Bolivia<br>Uruguay<br>Honduras Argentina<br>Venezuela<br>0 0.2 0.4 0.6 0.8<br>0 0.1 0.2 0.3 0.4 0.5 0.6<br>(c) In the CIVETS group, Colombia has the highest level (d) Among upper-middle income countries, only<br>of income inequality. Namibia has a higher Gini. Inequality in this group is on<br>the decline, while that of Colombia is increasing.<br>0.7 65.0 max (less<br>0.6 60.0 Namibia)<br>0.5 55.0 Colombia<br>50.0<br>0.4 median<br>45.0<br>0.3 average<br>40.0<br>0.2<br>35.0<br>0.1 30.0<br>0.0 25.0<br>20.0 min<br>15.0<br>1980s 1990s 2000s<br>(e) Since 1990 Latin American inequality has been (f) ... and eventually converged towards the highest in<br>declining. Meanwhile, Colombia‟s Gini increased... the region.<br>0.650 0.65<br>Maximum<br>0.600 Colombia 0.60 Maximum<br>Colombia<br>Colombia<br>Colombia Colombia<br>0.550<br>Median 0.55 Median<br>0.500 Average Average<br>0.50<br>0.450<br>0.45<br>0.400 Minimum Minimum<br>0.40<br>2005 2006 2007 2008 2009<br><!-- End of picture text --> Source: UNDP Human Development Indicators based on WDI data: (a) and (c). World Bank (2011): (b). WDI: (d). ECLAC database: (e) and (f). Note: The relative ranking of Colombia and Bolivia depends on the data source.

3
- Collier, Paul.  1999. “On the Economics Consequences of Civil War.” Oxford Economic <u>Papers, vol. 51: 168-83.</u>

- Collier, Paul. 1998. “The Political Economy of Ethnicity, " in B. Pleskovic and J.E. Stiglitz (eds) Annual Bank Conference on Development Economics, 1988, World Bank.

- Collier, Paul and Anke Hoeffler. 2006. “Grand Extortion: Coup Risk and the Military as a Protection Ratchet,” unpublished mimeo, The Centre for the Studies of African Economies, The University of Oxford.

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- Collier, P. and A . Garg. 1999. "On Kin Groups and Wages in the Ghanaian Labor Market", <u>Oxford Bulletin of Economics and Statistics, 61, pp. 133-52.</u>

Davis David and Joel N. Kuritsky. 2002. “Violent Conflict and Its Impact on Health Indicators in Sub-Saharan Africa, 1980 to 1997”. Paper presented at the annual meeting of the International Studies Association, New Orleans, LA, March.

- Durlauf, Steven. 2002. “Policy Evaluation and Empirical Growth Research,” in N. Loayza and R. Soto (editors).  Economic Growth: Sources, Trends and Cycles.  Central Bank of Chile, Santiago.

Duggan, Caterine. 2007. “Do different coups have different implications for investment? Some intuitions and a test with a new dataset”. Unpublished manuscript.

- Easterly, William. 2001a. “The Middle Class Consensus and Economic Development.” <u>Journal of Economic Growth,</u> vol. 6 (4):  317-35.

- Easterly, William. 2001b. “Can Institutions Resolve Ethnic Conflict,” <u>Economic Development and Cultural Change, vol. 49(4): 687-706</u>

- Easterly, William and Ross Levine. 1997. “Africa’s Growth Tragedy:  Policies and Ethnic Divisions,” November, Quarterly Journal of Economics _<u>.</u>_ CXII (4), 1203-1250.

- Easterly, W. and R. Levine. 2003.  Tropics, germs, and crops:  How endowments influence economic development.  Journal of Monetary Economics 50: 3-39.

37
_COTE D’IVOIRE: Growth, Specialization and the Terms of Trade_

# **Productivity Regression Data**

|**LNTERMS**|**lnYL**|**lnKL**|**lnIL**|**war**|
|---|---|---|---|---|
|0.195597075|13.56567206|13.50273294|11.89418359|0|
|0.01213893|13.63036667|13.62127714|12.12622101|0|
|0.021042458|13.61172432|13.64749306|11.74977866|0|
|0.151887531|13.71530307|13.72974085|12.10498303|0|
|0.25689101|13.84523414|13.8664145|12.43896993|0|
|0.029280476|13.78023699|13.95758233|12.3748589|0|
|0.029616206|13.85586063|14.04091473|12.42936888|0|
|0.029838754|13.86631216|14.09152501|12.33956417|0|
|0.029626057|13.94951388|14.13135339|12.32891306|0|
|0.189000861|14.00529411|14.18982621|12.47827683|0|
|0.251450053|14.06818833|14.2661494|12.63382669|0|
|-0.101907909|14.12263346|14.32056897|12.59311052|0|
|-0.17044778|14.12798729|14.35260476|12.5157202|0|
|-0.029818544|14.14973089|14.41213075|12.70813534|0|
|-0.000169234|14.15637593|14.45174492|12.65180422|0|
|-0.157882317|14.20042949|14.48416046|12.64456177|0|
|0.096952618|14.28760116|14.54573116|12.84352773|0|
|0.429270084|14.32429473|14.66200971|13.17257834|0|
|0.325652654|14.39422697|14.77892189|13.29067691|0|
|0.210898166|14.38446377|14.84979958|13.18454659|0|
|-0.329401347|14.23520265|14.85368109|12.8345015|0|
|-0.406058584|14.23716263|14.84849998|12.76269524|0|
|-0.440588359|14.20712239|14.82894764|12.63229558|0|
|-0.39604346|14.13548553|14.77965293|12.30467933|0|
|-0.20695394|14.07657855|14.67993138|11.36893371|0|
|-0.108144709|14.08917538|14.61392576|11.93065665|0|
|-0.090770041|14.09053262|14.56639144|12.09817457|0|
|-0.275403535|14.05678211|14.502942|11.83828643|0|
|-0.359202156|14.03819959|14.43531628|11.70781768|0|
|-0.530332274|14.03792584|14.36600448|11.6058994|0|
|-0.671972802|13.99795397|14.2813417|11.25386316|0|
|-0.594356155|13.95621218|14.19273022|11.33151038|0|
|-0.54704525|13.91247921|14.10299895|11.20845635|0|
|-0.452924182|13.87027389|14.03586067|11.45222126|0|
|0.012437816|13.8386791|13.97704984|11.4834388|0|
|0|13.86865956|13.94677499|11.71824886|0|
|-0.024464384|13.91042456|13.93213469|11.77879731|0|
|-0.035204369|13.93521491|13.92236837|11.79175492|0|
|-0.038491072|13.95210215|13.90524995|11.70794878|0|
|-0.023978592|13.94013457|13.8942581|11.73062068|0|
|-0.194188598|13.88870187|13.86642245|11.55075334|1|
|-0.204096314|13.86531137|13.81455389|11.25330228|1|
|-0.209580099|13.82169785|13.76282549|11.18410469|1|

33
# L **Introduction**

The competing conceptions of the large, unprotected or "informal" work force in developing countries differ greatly in their implications for the labor market reforms deemed essential to complement other liberalization measures,' as well as issues of "fair" competition in international trade.

The traditional view sees informality as the disadvantaged segment of a dualistic labor market segmented by legislated or union-induced rigidities and high labor costs in the protected or "formal" sector.<sup>2</sup> The large size of the sector thus testifies to the extent of inefficiencies in labor allocation and the magnitude of required reforms. Downward formal wage rigidity also implies strong predictions about sectoral interactions across time. In cyclical downturns, the informal sector is thought to absorb displaced formal sector workers, informal earnings falling relative to those in the formal sector, and then contract during recoveries as lhe queue for good jobs shortens again. A recent and related approach also postulates a long term trend where large enterprises, confronted by heightened competition in global manufacturing, increasingly sub-contract to unprotected workers as a means of reducing costs and gaining flexibility.3 The issue is thus particularly relevant to the debate over establishing common labor standards in regional free trade agreements.

# 'See, for example, World Bank (1995).

**2** The Harris-Todaro (1970) model is perhaps the traditional statement of this view. See also Sabot (1977), and Mazumdar (1983). An alternate view within the segmentation literature sees dualism as arising endogenously from efficiency wage type considerations that induce larger irmns to pay remuneration above market clearing (See Stiglitz, 1974; **Esfahani** and Salehi-Isfahani, 1989). See Rosenzweig (1988), Fields (1990), Thomas (1992), Tokman (1992), Portes and Schaufiler (1993), Portes (1994) for overviews.

3 See Piore and Sabel (1984), Beneria (1989), Port=s, Castells and Benton (1989), Portes and Schauffler (1989), Tokman (1992) and most recently articles in **Blank** and Freeman (1994). The U.S. Department of Labor has sponsored two studies on the informal sector: _Worikers Without Protections: Case Studies of the Informal Sector in Developing Countries_ (1993) and _The_ **_Infornal_** _Sector in Mexico_ (1992).
activity, we observe a fall in volume of production in all crops. Moreover, production in livestock and national non-agricultural activities also declines.

For example, food manufacturing contracts by 13 percent as there is a reduction in production of intermediate goods in this sector. As a result of the contraction in domestic production, import volume in almost all crops increases except for raw cotton, which experiences a fall in production and a rise in domestic prices. The most significant increase in import volume is seen in other grains with 65 percent as well as an increase in nuts by 45 percent. It is also important to note that manufactured food imports rise by 85 percent in volume. Export volume, on the other hand, decreases significantly following the fall in production in agriculture and an increase in domestic commodity prices.

We must also note that urban household’s real consumption decreases by about 3.3 percent, while that of rural households in all regions increases by 4 percent except in the East with a 1.6 percent increase (Table 4.16). We can attribute this disparity in rural and urban household response to differences in sources of income of these household types, and also the composition of consumption expenditures. Urban households earn about 40 percent of the total income due to labor, and the rest from capital, while rural households have income from land and water resources as well. While there is a clear drop in labor and capital income overall, there is a rise in rents to both irrigated and rainfed land, and a slight increase in the water factor income in the West and Central regions (which inhabit a large share of rural households). Nevertheless, there is a significant decline in real GDP by about 6 percent as a result of the fall in yields in rainfed crops by 30 percent simulating a shortage of water caused by climate change.

**Table 4.16. Change in disaggregated real household consumption**

||**Base**<br>**Level**|**%**|**Change**||
|---|---|---|---|---|
||<br>**(Million TRY)**|**Sc. 3.a**|**Sc. 3.b**|**Sc. 3.c**|
|**Urban HH**|192,526|-3.30|-4.00|-3.50|
|**West Rural**|28,136|4.10|4.50|5.80|
|**Central Rural**|11,422|3.70|3.90|-0.30|
|**East Rural**|8,662|1.60|1.50|0.60|
|**Southeast Rural**|2,450|2.40|2.00|-3.90|
|**LSCB Rural**|1,965|3.90|2.90|2.50|
|**Rural Total**|52,635|15.70|14.80|4.70|
|**Turkey**|245,161|-1.80|-2.40|-2.10|

_Source: Results from TACOGEM-W._ 56