rafmacalaba/datause-encoder-data huggingface dataset:
standardized wage differentials”). Standardizing female and male wages separately is less efficient, however, because there are almost no gender differences in reported pay, averaging, and period concepts within occupations, so there is no need to adjust for these concepts _within_ occupations. The only adjustments necessary are those to correct for differences in pay, averaging, and period concepts _across_ occupations, and this what is what we have done.<sup>10</sup> We have limited the heterogeneity of the data by limiting the pay concept to average, minimum, prevailing and median rates (excluding the maximum and ‘other’ rates). The ‘average’ pay concept is included because it is the preferred pay concept measuring the compensation of an average worker. We have also included the minimum and prevailing rates, however, because in the pre-1983 data this is a very common pay concept, and this will allow greater comparability over time. However we have excluded any observations where the reported minimum wage gender differential equals one –this is most likely a reflection of (non-discriminatory) statutory minimum rates rather than actual minimum rates. The median pay concept is only reported by the United States and has been retained to allow comparison with other research on US data.

The estimated adjustment factors are very small for the pay and period concepts. For the averaging concept there is a relatively large adjustment for minimum wages: the occupational gender wage gap is estimated to be 6 % point higher for minimum wages as opposed to average wages. The estimated adjustment factors have been used to transform each observed gender wage gap into a gender wage gap for average hourly earnings. It is the latter standardized gender wage gap that we have used for the analysis.<sup>11</sup>

> 10 We did some preliminary analysis on standardized female and male wages, however, with few significant results. This is probably the result of loss of efficiency by standardizing female and male wages separately, rather than standardizing the wage differential directly.

> 11 Note that in the standardizing regressions we are assuming that the effect of the differences in concepts is the same across countries.  If we had enough variation within the countries it would be possible to estimate country-specific adjustment factors. In our earlier standardization procedure for wages we have explored this issue by introducing country-specific adjustment factors (see Freeman and Oostendorp 2000). Because of lack of variation within countries, this could only be done for female-male wage differentials within countries, but not for differences in the pay, averaging and period concepts. Hence, when standardizing the gender wage gap itself, we do not have enough variation to estimate country-specific adjustment factors for  the pay, averaging and period concepts. We have, however, also followed an intermediate route, and estimated adjustment factors specific for income levels. We found that allowing for income level-specific adjustment factors gives virtually the same results (available on request from the author).

10
Reinikka and Svensson (2002), using firm data from Uganda, find that weak public infrastructure lowers private investment, thus lowering capital intensity. Some firms do respond by investing in private solutions to problems in unreliable electricity and transportation, but they find the installed capital is often of lower quality when there is little complimentary public investment available.

Svensson (2005) notes that there is a significant correlation between corruption and a country’s level of income. He finds that the level of corruption in SSA, while higher than in more developed countries, is where it would be expected given its lower level of income. This reinforces the importance of controlling for basic country differences, including GDP per capita, in cross-country regressions, or for looking at differences within countries.

Fisman and Svensson (2007) use panel data from Uganda to show that corruption has significant effects in lowering sales growth. They find the effect of paying bribes to be three times larger than the effect of taxes. However, bribes can act as grease money, speeding up processes and delivering positive results. It will be interesting to test here for the effects in the broader set of countries and whether they differ across regions.

Beyond the direct benefits to individuals of expanding employment opportunities, there are additional benefits to having firms grow. One is the effect on productivity. With greater economies of scale, firms can raise their productivity and use their inputs more efficiently. They can be more likely to adopt more advanced technologies, reinforcing greater productivity (Collier, 2000; Bigsten and Soderbom 2006). And size has been found to be a significant predictor of the probability of exporting, controlling for sector and capital intensity (Rankin et al. 2006). Given the smaller market size in SSA, this offers a significant way to expand market opportunities. It has also been found to have ‘learning-by-exporting’ benefits as firms gain greater knowledge about additional production, managerial and distribution techniques (Bigsten et al. 2003; Van Biesebroeck 2005).

10
consumption estimates for Mogadishu. The resulting consumption aggregate is presented with consistency checks for its validation.

# **Ex post Simulation**

The rapid consumption methodology is applied _ex post_ to household budget data collected in Hargeisa, Somalia. Hargeisa was chosen as it is the most similar city to Mogadishu. Using the full consumption data set from Hargeisa allows a full‐fledged assessment of the new methodology. Based on selected indicators, the results are compared after estimating consumption based on the rapid consumption methodology with the results from using the traditional full consumption module. A comparison is added with the results for a reduced consumption module.

The simulation assigns each household to one optional module. The consumption data for the modules not assigned to the household is deleted. Multiple simulations are performed with varying assignment of modules to households. Across the simulations, three consumption aggregates and four poverty and inequality indicators are calculated. The consumption indicators capture the accuracy of the estimation at three different levels: the household level, the cluster level (consisting of about 9 households) and the level of the data set. In addition, the poverty headcount (FGT0), poverty depth (FGT1) and poverty severity (FGT2) as well as the Gini coefficient are calculated to capture inequality.

The six proposed estimation techniques presented in the previous section are compared based on 20 simulations with respect to their relative bias and relative standard error. All simulations used the same item assignment to modules using the algorithm as described with parameter _d=3_ (see Table 1 for the resulting consumption shares per module).<sup>7</sup> The estimation techniques differ considerably in terms of performance. The techniques are also compared to using a reduced consumption module where the same consumption items are collected for all households. The number of items is equal to the size of the core and one optional module implying a comparable face‐to‐face interview time to the Rapid Consumption methodology.

> 7 Robustness checks are performed with different item assignment to modules including setting the parameter _d=1_ and _d=2_ . The estimation results are extremely robust to changes in the item assignment to modules.

10
iProfessional.com. 2007. “Nueva batería de medidas para contener el avance chino.” August 17. http://www.iprofesional.com/notas/51699-Nueva-batera-de-medidas - para-contener-el-avance-chino.

- Kuhn, Thomas S. 1996. The Structure of Scientific Revolutions (3rd ed.). University of Chicago Press.

- Lakoff George. 2006. “Simple Framing:  An introduction to framing and its uses in politics,” Rockridge Institute. Available at http://integraloptions.blogspot.com/2009/04/simple-framing-by-george-lakoff.html.  Accessed April 30, 2012.

Longoni, Matías. 2010. “China levanta la prohibición y vuelve a comprar aceite de soja.” <u>Clarín, Octubre 12. http://www.clarin.com/politica/China-levanta-</u> prohibicioncomprar-aceite_0_352164842.html.

- Lowenthal, Abraham F. 2011. “Disaggregating Latin America: Diverse Trajectories, Emerging Clusters and their Implications,” Brookings Research and Commentary, 01 November, 2011, The Brookings Institution. at

http://www.brookings.edu/papers/2011/1101_latin_america_lowenthal.aspx. accessed Aug. 20 2013

- Ministry of Industry. 2011a. “Garbarino presentó un proyecto de inversión para fabricar tablets en Tierra del Fuego.” Press Release, January 20. http://www.industria.gob.ar/ garbarino-presento-un-proyecto-de-inversion-para-fabricar-tablets-en-tierradelfuego/.

- ———. 2011b. “Giorgi: Este gobierno cree y aplica administración del comercio.” Press Release, February 25. http://www.industria.gob.ar/giorgi-este -gobierno-cree-yaplica-administracion-del-comercio/.

———. 2011c. “La defense del mercado interno es un pilar fundamental para el crecimiento de la economía.” Press Release, February 22. http://www.subindustria.gob . ar/ blog/2011/02/22/%e2%80%9cla-defensa-del-mercado-interno-esun-pilar - fundamental-para-el-crecimiento-de-la-economia%e2%80%9d/.

———. 2012. “Giorgi: “el que más rápido integre piezas nacionales es el que más va a ganar.” Press Release, March 22. http://www.industria.gob.ar/ giorgi-el-que-masrapido-integre-piezas-nacionales-es-el-que-mas-va-a-ganar/.

- Maddison, Angus. 2007.  Contours of the World Economy 1-2030 AD, Oxford University Press.

- McCarthy, Nigel. 2000. “Alf Rattigan and the journalists: advocacy journalism and agenda setting in the Australian tariff debate 1963-1971,” Australian Journalism <u>Review, 22(2): 88-102.</u>

- Nogués, Julio J. 2011. Agro e Industria: del centenario al bicentenario, Cuidad Argentina y Hispania Libros.

- Nogués, Julio J. 2011a. Agricultural Export Barriers and Domestic Prices: Argentina during the Last Decade, mimeo, prepared for FAO and available from the author.

29
40 Table 12: Fraction of wage employment growth accounted for by public sector growth in selected developing countries.

|Country:|Period:|Average|growth (% per|annum)|Percentage share of<br>public sector in|
|---|---|---|---|---|---|
|||Public|Private|Total|increase of total wage<br>employment|
|Brazil|1973-83|1.4|0.0|0.3|92|
|Costa Rica|1973-83|7.6|2.8|3.5|34|
|Egypt|1966-76|2.5|_-O.S_|2.2|103|
|Ghana|1960-78|3.4|-S.9|-0.6||
|India|196080|4.2|2.1|3.2|71|
|Kenya|1963-81|6.4|2.0|3.7|67|
|Panama|1963-82|_7.5_|1.8|2.7|45|
|Peru|1970-84|6.1|-0.6|1.1|140|
|Sri Lanka|1971-83|8.0|0.9|3.9|87|
|Tanzania|1962-76|6.1|-3.8|1.6|190|
|Thailand|1963-83|6.3|5.5|5.7|33|
|Venezuela|1967-82|5.1|3.4|3.7|27|
|Zambia|1966-80|7.2|-6.2|0.9|418|
|Unweighted<br>mean||_5.5_|0.3|2.4||
|Source: Derived|from Gelb, Knig|ht, and Sabot, 1|991, table 1.|||

The persistence of negative institutional incentives is often built into the system because by and large the most educated control the access to power-2. Selection into the elite national civil service in China well into the twentieth century was based on an exam that rewarded detailed knowledge of 52 Another fun quote from North (1991): But so too, can unproductive paths persist. The increasing returns characteristic of an initial set of institudons that provide disirentives to productive activity will create organizations that interest groups with a stake in the exisdng constraints. They will shape the polity in their interests. Such institutions provide incentives that may encourage military domination of the policy and economy, religious fanaticism or plain, simple redistributive orgapiation, **but** they provide few rewards from ieases in the stock and dissemination of economically useful knowledge. (p 99)
sample size to ensure that a sufficiently large variation in household types was captured to assign and interpret the impact of particular taxes and benefits. As a result, the analysis is primarily based on the PIS. In order to capture the impacts of indirect taxes on consumption, the analysis employed survey-to-survey imputation to assign consumption to each household, as detailed in Appendix 2.

Household survey data are combined with data from National Income Accounts and public finance accounts from the Ministry of Finance. This included information on consolidated central government budgets, Local government budgets, and annual reports from the Central Bureau of Statistics on various sectors.

# **Approach**

To analyze the incidence of each fiscal intervention, and the impact of taxes and social spending on poverty and inequality, we follow the Commitment to Equity (CEQ) approach of Lustig (2017) and measure per capita income before and after each fiscal intervention as described in Figure 1. In particular, for every household we define the following income concepts:

- _Market income_ includes pre-tax and pre-contribution wages, salaries, and income earned from capital assets (rent, interest or dividends) and private transfers.

- _Disposable income_ is constructed by adding direct transfers and subtracting direct taxes and social contributions to market income. The direct taxes considered in the case of Croatia include personal income taxes, surtaxes, taxes on vessel, road motor vehicles and vacation homes.

- _Consumable income_ subtracts indirect taxes from disposable income. In Croatia, indirect taxes included in this analysis include the VAT, excises on alcohol and tobacco, fuel and automobiles, and other indirect taxes (not classified as VAT or excises).

- _Final income_ adds in-kind benefits in the form of health and education to consumable income.

One area where there is no clear consensus in the literature is on how to treat contributory old-age pensions and the related contributions. Arguments exist in favor of treating contributory pensions as individual savings or deferred income, while others argue that they should be treated as a government transfer, with the related contributions being treated as a direct tax. Following Lustig (2017), we present three scenarios. Under our “main” scenario we treat old-age pensions as deferred income, and the corresponding contributions are treated as savings. In an alternative scenario, contributory old-age pensions are treated as transfers and added to market income. The corresponding contributions are treated as taxes and thus subtracted from market income to generate disposable income, in line with standard EU measurement of disposable income. Finally, in a third scenario in which the first pillar of the pension system (the pay-as-you-go pillar) is treated as a transfer, while the second pillar is treated as deferred saving. The alternative scenarios are presented in Appendix 3.

10
in that sector. Thus the coefficient ∆ _r_ should be negative. From the expression of ∆ _r_ , it follows that _the average price premium for the formal sector should be higher than the average rent premium_ .

Note, however, that in the context of our model, equation (14) contains endogenous variables on the right-hand side, since investment (which would correspond to the _X_ ’s) and rate of return are two endogenous variables, determined by the same exogenous variable, the destruction rate _d_ . Thus, ∆ _r_ cannot be interpreted as a causal effect of _F_ on _r_ . However, following the same empirical approach for Pune, India, we find that the _X_ ’s are very weakly correlated to rates of returns. Besides, the differential between the formal and informal sector estimated this way is ∆ _r_ = 20 percent, very close to our previous estimations. Extrapolating to the aforementioned studies, we conclude that this technique may be used to obtain a measure of the investor’s premium. Results from estimation of equations (13) are presented in Table 6. Results conform to intuition, and the explanatory power of variables lies in the upper range of what is usually obtained in similar case: the R-square for rents is _._ 62, that for prices is _._ 63.

Most of the explanatory variables have the expected signs. Firstly, both rents and prices are higher in formal category, which is reflected by the positive coefficient on the formal dummy. Residents are willing to pay higher rents if the dwelling unit has more rooms, kitchen, if there is proper sewerage, good toilet facilities, closer to public transport facilities measured in terms of time to nearest bus stop. Moreover, households are willing to pay higher rents for increased hours of water supply irrespective of the source. These results are very similar when we look at sale prices instead of rents. However, it is interesting to note that households’ willingness to pay in terms of rents are lower if they have to invest in individual water connection or get an individual sub-connection for water supply. Furthermore, rents are much lower if it relies on community tap as a source for water supply. The results are similar when we look at prices but they are not significant.

Our investment model can be used to estimate a destruction risk for Davao, 1979, and Manilla, 1983. From Jimenez’ (1984) results for Davao, the figure corresponding to the 22
- [5] Andrews, D. and J. Monahan (1992): "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator", Econometrica 60, 953-966.

- [6] Bai, J. (2003): "Inferential theory for factor models of large dimensions", Econometrica 71, 135-71.

- [7] Bailey, N., G. Kapetanios and H. Pesaran (2015): "Exponent of cross-sectional dependence: estimation and inference", Journal of Applied Econometrics

- [8] Bekaert, G., and A. Mehl (2017): “On the global ...nancial integration ’Swoosh’and the Trilemma”, unpublished manuscript.

- [9] Bluedorn, J., R. Duttagupta, J. Guajardo and P. Topalova (2013): "Capital ‡ows are ...ckle: anytime, anywhere", IMF Working Paper 13/183.

- [10] Breitung, J. and S. Eickmeier (2016): "Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches", in E. Hillebrand and S.Koopman (eds.), Advances in Econometrics vol 33.

- [11] Broner, F., T. Didier, A. Erce, and S. Schmuker (2013): "Gross capital ‡ows: dynamics and crises", Journal of Monetary Economics 60, 113-133.

- [12] Bruno, V. and H. Shin (2015a): "Capital ‡ows and the risk-taking channel of monetary policy", Journal of Monetary Economics 71, 119-132.

- [13] Bruno, V. and H. Shin (2015b): "Cross-border banking and global liquidity", Review of Economic Studies 82, 535-564.

- [14] Byrne, J. and N. Fiess (2011): “International Capital Flows to Emerging and Developing Countries: National and Global Determinants, ” Journal of International Money and Finance 61, 82-100.

- [15] Calvo, G., L. Leiderman and C. Reinhart (1996): "In‡ows of capital to developing countries in the 1990s", Journal of Economic Perspectives 10, 123-139.

- [16] Cerutti, E., S. Claessens, and D. Puy (2017): "Push factors and capital ‡ows to emerging markets: why knowing your lender matters more than fundamentals", unpublished manuscript.

- [17] Cerutti, E., S. Claessens, and L. Ratnovski (2017): "Global liquidity and cross-border bank ‡ows", Economic Policy, 81-125.

- [18] Cerutti, E., S. Claessens, and A. Rose (2017): "How important is the global ...nancial cycle? Evidence from capital ‡ows", CEPR Discussion paper 12075.

- [19] Choi, I. (2012): "E¢ cient estimation of factor models", Econometric Theory 28, 274308.

- [20] Choi, I. (2017): "E¢ cient estimation of nonstationary factor models", Journal of Statistical Planning and Inference 183, 18-43.

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- 35 -

# XII. FUELVOOD STUKPAGE FEB SYSTEMS IN PRACICE

3.1 In the preceding sections, we have presented the economic justification for charging fees for fuelwood stumpage and described various methods usod for estimating stumpage values. This section looks at the practical application of stumpage fees.

3.2 Today, not all countries charge a stumpage for fuelwuod, Botswana being a case in point. Also, most LDCs do not charge for fuelwood if it is for self cousumption because it is difficult if not impossible to collect from a large number of self consumers. However, as soon as wood products become commercialized, the levying of fees is possible especially if production is concentrated.

3.3 The bulk of wood raw material, especially fuelwood, originates from government land. Therefore, examples of stumpage fee systems will be given from state forest services. In some LDCs private individuals or institutions grow wood for sale. The individual will try to maximize the income from the sale of wood and would take into consideration end use or uses an.d distance from the market. This is only partially done by forest services as the examples from four African countries--Zambia, Malawi, Rwanda and Niger--will illustrate.

3.4 Table 3.1 shows the Zambian government's revised fees for forest products, published in March, 1988. In principle the fees are a flat rate but they vary according to end use, species, or product size.

3.5 The table illustrates a number of problems mentioned in Section I:

- (a) Flat rate fees on products ignore the variable of distance from the markets. Transport costs can greatly influence the selling price of a wood product, especially firewood and charcoal; a charcoal producer near the market can sell a sack of charcoal for a much higher price than one remote from the market. Thus the grower of the wood raw material should be able to command a higher price if he is situated close to the market;

- (b) In Zambia, wood for fuel is sold not standing but either stacked or as a fee on the finished charcoal product. Though it is easier and less time-consuming to charge for the semifinished or finished product than to charge for the wood raw material (the standing tree), this is only a second-best solution. Charging for the product lessens the incentive of the buyer to make full, efficient use of the material. For instance, if a charcoal producer pays only for the wood removed in the form of charcoal (and perhaps some poles), he has little incentive to use all sizes of wood, a greater mix of species, to process the wood efficently, and to try to market all of his charcoal, including the powder and fines. One way around this
|**Table 4:**R|IF-IV regre|ssion coeffic|ients for fem<br>**EGYPT**|ale labor forc|e participat|ion, by cou|ntry.|
|---|---|---|---|---|---|---|---|
||**IN**|**DIA**|**,**<br>**ARAB REP.**<sup>**a**</sup>|**MOROCCO**<sup>**a**</sup>|**JORDAN**<sup>**a**</sup>|**BR**|**AZIL**|
|_Decile_|_Coefficient_|_Hausman test_|_Coefficient_|_Coefficient_|_Coefficient_|_Coefficient_|_Hausman test_|
|_1_|72.76***|636.56***|0.14|0.06|0|11.09***|1880.57***|
||[12.84]||[0.14]|[0.09]|[0.01]|[0.28]||
|_2_|64.52***|642.89***|-0.06|0.07|-0.01|9.88***|2022.65***|
||[11.35]||[0.09]|[0.06]|[0.01]|[0.22]||
|_3_|72.88***|651.89***|-0.04|0.15**|0.03**|10.59***|2060.85***|
||[12.82]||[0.10]|[0.06]|[0.01]|[0.21]||
|_4_|79.69***|66787***|0.05|0.12**|0.06***|10.08***|207167***|
||[14.02]|.|[0.11]|[0.05]|[0.01]|[0.21]|.|
|_5_|91.56|66911***|0.09|0.15**|0.08***|11.06***|207328***|
||[16.11]|.|[0.12]|[0.05]|[0.01]|[0.20]|.|
|_6_|105.17***|67209***|0.17|0.19***|0.11***|10.70***|207234***|
||[18.50]|.|[0.11]|[0.05]|[0.01]|[0.20]|.|
|_7_|126.08***|67490***|0.03|0.17**|0.14***|11.55***|208043***|
||[22.19]|.|[0.14]|[0.06]|[0.02]|[0.24]|.|
|_8_|148.90***|67732***|-0.08|0.31***|0.22***|14.42***|206756***|
||[26.20]|.|[0.18]|[0.06]|[0.02]|[0.24]|.|
|_9_|197.48***|681.23***|0.11|0.48***|0.31***|17.69***|2087.54***|
||[34.80]||[0.22]|[0.09]|[0.04]|[0.32]||
|_Percentile_<br>_ratio_|_Coefficient_|_Hausman test_|_Coefficient_|_Coefficient_|_Coefficient_|_Coefficient_|_Hausman test_|
|_P90/P10_|19.22***<br>[3.48]|253.11***|0.00<br>[0.03]|0.05**<br>[0.01]|0.05***<br>[0.00]|0.07<br>[0.04]|357.21***|
|_P80/P20_|13.64***|22008***|0.00|0.03**|0.03***|0.22***|20690***|
||[2.42]|.|[0.02]|[0.01]|[0.00]|[0.02]|.|

30