rafmacalaba/datause-encoder-data huggingface dataset:
ternative methods of identifying public decision makers arises in many domains of society, including government. For instance, decentralization reforms frequently create new democratic institutions at the local level, such as municipal councils, mayors, management committees, etc. Whenever new institutions are created, it is a first-order concern to ensure that they serve the collective interests of their constituents, rather than becoming vehicles for rent extraction (Myerson, 2015). Similar institutional design questions arise outside of government, for example in community development programs (where a major concern is the capture of projects by local elites (Mansuri and Rao, 2013)), in membership-based organizations (e.g. associations, cooperatives (Grossman, 2014), or user groups), and in corporate governance. In each of these cases, the need to minimize opportunities for embezzlement or rent extraction is a universal concern.

A small but growing number of rigorous experimental and observational studies have begun to systematically compare democratic elections to other types of political institutions, including traditional authorities (Baldwin and Mvukiyehe, 2015; Beath et al., 2014), single-party rule (MartinezBravo et al., 2014), direct democracy (Olken, 2010), and bureaucratic appointments (Alatas et al., 2013; Lierl, 2014). Of these, Alatas et al. (2013); Beath et al. (2014) and Lierl (2014) directly focus on the embezzlement of public resources. Alatas et al. (2013) find no difference in embezzlement outcomes between elected and appointed village leaders in Indonesia. Lierl (2014) finds that elected village leaders in Tanzania are more benevolent than appointed village leaders with regard to their social preferences, but that embezzlement outcomes become indistinguishable once social and reputational incentives are taken into consideration. Beath et al. (2014) find that the existence of elected village councils alongside traditional authorities in Afghanistan increased embezzlement overall, but reduced embezzlement if the councils were given exclusive decision authority. These ambiguous results suggest that the impact of democratic elections on embezzlement is context-dependent, which shifts the focus towards understanding the underlying causal mechanisms.

In this paper, elected decision makers will be compared to randomly selected decision makers, which is a particularly useful comparison case to illuminate the causal mechanisms by which elections can affect embezzlement outcomes. First, random selection is a benchmark against which electoral selection effects can be quantified. In sufficiently large numbers, randomly selected de6
# **V. Conclusion**

This study established a negative relationship between family management and the quality of management practices, leveraging a unique dataset using a special module spanning 41 developing and advanced economies. The results confirm what has been found in the literature, although the sample in this study is of a different nature, including many firms in regions that have not been covered elsewhere. The study extends the literature by examining how external factors could attenuate or exacerbate the negative relationship between management practices. Corruption, competition, and political connections accentuate, while stringent regulations and innovation ameliorate the relationship between family management and the quality of management practices. Furthermore, when all management is from the same family, these firms perform poorly on the management practices dimensions of the number of performance indicators monitored, knowledge of production or service provision targets, and not surprisingly, the basis of promotion. Finally, a mix of family and non-family managers may not be as detrimental to management practices as having all management be family members.

What is also established is the lack of statistical significance in certain relationships. Family ownership, firm size, exporter status, foreign ownership, manufacturing sector, and female managers do not play any significant role (neither exacerbate nor attenuate) in the relationship between family management and management practices. Furthermore, for larger firms, family managers do not exhibit any statistically significant difference compared with non-family managers with regards to how they allocate (or appear to allocate) their time to interact with other decision makers, suppliers, and employees as measured by frequency of meetings. This information is leveraged from a special set of questions on time use for large firms in the sample.

While the study makes significant strides in the literature, it is also important to note the limitations. Endogeneity concerns are difficult to alleviate given the cross-sectional nature of the data. Furthermore, the survey data do not contain information on whether the family owners are the founders, or descendants of the founders, which has been found to be important in the literature (Villalonga and Amit, 2006). Regardless, this study makes an important contribution by highlighting the role that the external operating environment can have in the relationship between family management and management practices. The key implication is that the business environment matters, and for some cases it may be easier to address some of these concerns than to change the management or ownership structure of family firms.

12
- 27 -

(Bracey, in Caully, 1981). And, inevitably, accountability pressures from the state have led to conflicts between the state agency and local school districts.

Despite these problems, the accountability dimension of evaluation is likely to continue to dominate U.S. practice. Evaluators are now seeking ways to adapt their methods and approaches to this powerful factor in educational policy and decision-making.

The major adaptation has been general acceptance of the place of evaluation in school management, of the formative purposes of monitoring and evaluation processes. Thus the role of the evaluator has changed from that of the independent critic or researcher to that of a participant in the process of program improvement (Eichelberger, 1986: pp. 30-33).

Adaptation has also involved significant movement away from the rigorous standards of social science research towards more pragmatic approaches which provide timely information for decision- making. These approaches recognize that the users of evaluation are "... less concerned than academics with reducing the final few grains of uncertainty about knowledge claims, ... are more willing to trust their own experience and tacit knowledge for ruling out validity threats ... [and] they also expect to act upon whatever knowledge base is available, however serious its deficiencies.' (Cronbach, cited in Cook, 1986: p. 219).

# Summary

Educational evaluation in the United States began -- and has ended - - in schools and communi4:ies. Along the way an important excursion was taken into the realm of large scale research evaluation studies at the national level. The weakness of such studies in providing information useful to decision-makers seeking to improve education at local levels in a decentralized and diverse system of education led to their abandonment. In their place we now find eclectic approaches that meet the demands of utilization and accountability, include assessment of implementation processes, and emphasize achievement testing and monitoring systems that provide a continuous base of information on school operations. We also find -- parallel emergence of research centered on the factors that make schools not schooling -- more effective.

School accreditation systems, both voluntary and public, have provided an important level of institutional assessment. This, in turn, has helped protect the public against poor educational institutions and has helped administrators improve the quality of their schools.

The federal government played a crucial role in this process Evaluation requirements and funding, tied to programs that financed educational change and improvement, made evaluation an increasingly integral part of educational practice. Federal funding initiated and sustained the development of evaluation capacity, through the establishment of State education agencies and the nurturing of the evaluation profession.
Figure 1 presents a scatter plot of the empirical joint distribution of claim payments and subdistrict average yields, and a kernel plot of the average claim payments conditional on the yield. The relationship between WBCIS claim payments and yields appears to be rather weak, with low average claim payments in the event of extreme yield losses; the leftmost point estimate of the kernel regression indicates that in the event of a zero yield, the average WBCIS claim payment is only 12% of the sum insured while in the event of yields being twice the historical average, the average WBCIS claim payment is 6% of the sum insured.

Considering the entire empirical joint distribution, the average Pearson product-moment correlation coefficient is -14% and the average Spearman's rank correlation coefficient is -13%. (In both cases a more negative coefficient indicates lower basis risk.) While these correlations are the correct sign, the magnitudes are quite low. Moreover, for some crops the average correlation is the wrong sign, with lower yields associated with lower claim payments.

9
Table 2: Studies assessing macroeconomic consequences and economic vulnerability to natural hazards.

|**Study**|**Vulnerability variables for predicting**<br>**economic impacts and risk**|**Response variables**|
|---|---|---|
|Charveriat, 2000|• Size of the economy, degree of<br>diversification and size of the<br>informal and agricultural sectors.|• GDP|
|ECLAC and IDB,<br>2000;<br>Freeman et al.<br>2002;<br>Mechler,2004;<br>Hochrainer, 2006|• Ability to refinance losses and<br>provide relief to the affected<br>population (financial vulnerability)<br>• Availability of implicit (aid) and<br>explicit (insurance) risk sharing<br>arrangements|• GDP, fiscal variables|
|Burton et al.,1993;<br>Kahn, 2005.|• Income|• Deaths due to natural<br>disasters|
|Benson and Clay,<br>2004|• Structure of the economy<br>• Size<br>• Income level and stage of<br>development<br>• Prevailingsocioeconomic conditions|• Total GDP annual change<br>• Agricultural GDP annual<br>change<br>• Non-Agric. GDP annual<br>change|
|Toya and<br>Skidmore, 2007|• Educational attainment in population<br>aged 15 and over<br>• Economic openness<br>(exports+imports)/GDP<br>• Financial sector level of development<br>(M3/GDP)<br>• Government consumption<br>• Additional variables that determine<br>the deaths caused by disasters<br>(population,land area,disaster type).|• Disaster-related deaths<br>• Damages/GDP|
|Noy, 2009|• Literacy rate<br>• Quality of institutions<br>• Per capita income<br>• Openness to trade<br>• Levels of government spending<br>• Foreign exchange reserves<br>• Levels of domestic credit<br>• Openness of capital accounts|• GDP|
|Raschky, 2008|• Availability of financial risk sharing<br>institutions|• GDP|

Source: extended from Barrito, 2008.

10
# Hazard ratio estimates from a stratified Cor model for transitions to polygamy

|Wife controls||
|---|---|
|Age at marriage|O.977|
||(0.018)|
|Serere ethnicity|0.630<br>|
||(0.257)|
|Pulaar ethnicity|1.036<br>|
||(0.385)|
|Minority ethnicity|1.062|
|Ref: Wolof ethnicity|(0.334)|
|Fostered before 15|0.668**|
||(0.124)|
|No formal education|1.709**|
||(0.416)|
|Secondary education or higher<br>|1.350<br>|
|Ref: Primary education|(0.487)|
|Husband controls||
|Age at marriage|0.960***|
||(0.011)|
|Serere ethnicity|0.974<br>|
||(0.393)|
|Pulaar ethnicity|0.636|
||(0.238)|
|Minority ethnicity|0.733|
|fief: Wolof ethnicity|(0.235)|
|Fostered before 15|1.581***|
||(0.205)|
|No formal education|1.298<br>|
||(0.257)|
|Secondary education or higher<br>|1.005<br>|
|Ref: Primary education|(0.294)|
|Union controls||
|Dakar region|0.833|
||(0.147)|
|Other urban area|0.729%|
|Ref: Rural area|(0.135)|
|Additional controls?|‘Yes|
|Numberofobservations|1356|

Semi-parametric Cox proportional hazard model stratified by the polygamy status of the husband's father; exponentiated coefficients are presented (hazard ratios); robust standard errors in parentheses

* p< 0.10, ** p < 0.05, *** p< 0.01

The estimation sample includes all monogamous unions and polygamous unions made of husband and first-rank wife aged 15 to 60, in the first wave of the PSF Survey.

7 Additional controls include dummies for Koranic education of both spouses’ parents, and for formal education and sectors of activity of both spouses’ fathers. Data source: PSF Survey, wave 1 (2006-2007)
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# _5.2.3 Somalia_

Like Nigeria, there are no significant gender gaps in education in Somalia, but the differences in deprivation levels by displacement status are stark (Table 9). For example, over 95% of displaced individuals, poor or otherwise, are deprived in the years of schooling indicator, compared to six out of ten non-displaced individuals in the wider population. Meanwhile, women are more deprived in employment only among the nondisplaced population, and the gap is larger among the poor. The gender gaps in legal identification are significant only among the wider population, where women are more deprived overall.

_Table 9: Proportion of deprived individuals across displacement status by gender, Somalia_

||IDPs<br>|||Non-IDPs<br>|<br>||
|---|---|---|---|---|---|---|
||Male|Female|Difference|Male|Female|Difference|
|_All households_|||||||
|Years of schooling|0.97|0.97|0.00|0.60|0.63|-0.03|
|School attendance|0.64|0.68|-0.04|0.59|0.63|-0.03<sup>*</sup>|
|Unemployment|0.08|0.10|-0.01|0.06|0.11|-0.05<sup>***</sup>|
|Legal identification|0.83|0.86|-0.03<sup>**</sup>|0.83|0.86|-0.03<sup>***</sup>|
|Early marriage|0.24|0.55|-0.31<sup>***</sup>|0.17|0.53|-0.35<sup>***</sup>|
|_MPI poor households_|||||||
|Years of schooling|1.00|0.99|0.01|0.83|0.87|-0.04|
|School attendance|0.72|0.75|-0.03|0.81|0.84|-0.03<sup>*</sup>|
|Unemployment|0.11|0.13|-0.01|0.10|0.17|-0.07<sup>***</sup>|
|Legal identification|0.90|0.92|-0.02|0.97|0.97|-0.01|
|Early marriage|0.26|0.59|-0.33<sup>***</sup>|0.21|0.67|-0.46<sup>***</sup>|

Source: Authors’ calculations using the Somalia HFS (2017). Significance at 1% ***, 5% **, and 10% * levels.

Early marriage rates are significantly higher among women than men in both displaced and non-displaced communities, although the gender gaps are larger among the nondisplaced. Among the MPI poor, non-displaced women also see higher levels of deprivation than their displaced peers.

# _5.2.4 South Sudan_

In South Sudan (Table 10), the gender gaps in education are significant only for the host community, when comparing men and women’s rates of primary school completion 20
# **Table 8: Income Difference Regression 1993-2000**

||`(1)`|`(2)`|`(3)`|`(4)`|
|---|---|---|---|---|
|`Dependent variable`|`C`|`hange in log`|`real inco`|`me`|
|`Log Real Income 1993`|`-0.623`|`-0.570`|`-0.632`|`-0.581`|
||`(23.32)**`<br>|`(17.92)**`<br>|`(23.64)**`<br>|`(18.19)**`<br>|
|`Age`|`0.043`|`0.043`|`0.040`|`0.040`|
||`(2.50)*`|`(2.48)*`|`(2.38)*`|`(2.37)*`|
|`Age Squared`|`-0.001`|`-0.001`|`-0.001`|`-0.001`|
||`(2.96)**`|`(2.94)**`|`(2.91)**`|`(2.90)**`|
|`Sex`|`0.446`|`0.443`|`0.481`|`0.478`|
||`(9.85)**`<br>|`(9.82)**`<br>|`(10.19)**`<br>|`(10.17)**`<br>|
|`Working hours per month`|`-0.002`|`-0.002`|`-0.002`|`-0.002`|
||`(7.44)**`|`(7.37)**`|`(7.31)**`|`(7.24)**`|
|`Change in Working hours per`|`-0.001`|`-0.001`|`-0.001`|`-0.001`|
|`month`|||||
||`(5.98)**`|`(6.11)**`|`(6.08)**`|`(6.21)**`|
|`Wage Income Dummy`|`-0.032`|`-0.028`|`-0.036`|`-0.032`|
||`(0.78)`|`(0.71)`|`(0.76)`|`(0.69)`|
|`Years of schooling`|`0.064`|`0.064`|`0.057`|`0.057`|
||`(11.90)**`|`(11.87)**`|`(10.00)**`|`(9.99)**`|
|`Household size`|`0.048`|`0.046`|`0.046`|`0.045`|
||`(3.22)**`|`(3.12)**`|`(3.13)**`|`(3.04)**`|
|`Change in household size`|<br>`0.036`|<br>`0.039`|<br>`0.033`|<br>`0.036`|
||`(1.46)`|`(1.59)`|`(1.34)`|`(1.47)`|
|`Number of Children < 5`|`-0.090`|`-0.088`|`-0.081`|`-0.079`|
||`(2.20)*`|`(2.16)*`|`(2.00)*`|`(1.96)`|
|`Change in the number of`|`0.051`|`0.049`|`0.042`|`0.040`|
|`children < 5`|||||
||`(1.49)`|`(1.45)`|`(1.25)`|`(1.20)`|
|`Number of Men in hh`|`-0.036`|`-0.035`|`-0.036`|`-0.036`|
||`(1.64)`|`(1.60)`|`(1.69)`|`(1.65)`|
|`Change in Number of Men in`|`-0.030`|`-0.033`|`-0.028`|`-0.031`|
|`hh`|||||
||`(0.91)`|`(1.02)`|`(0.86)`|`(0.98)`|
|`Urban Dummy`|`-0.052`|`-0.049`|`-0.043`|`-0.039`|
||`(1.30)`|`(1.20)`|`(1.06)`|`(0.97)`|
|`North Sumatra`|`-0.167`|`-0.237`|`-0.157`|`-0.224`|
||`(1.87)`|`(2.58)**`|`(1.76)`|`(2.44)*`|
|`West Sumatra`|`-0.185`|`-0.245`|`-0.195`|`-0.253`|
||`(1.59)`|`(2.09)*`|`(1.68)`|`(2.16)*`|
|`South Sumatra`|`-0.062`|`-0.088`|`-0.042`|`-0.067`|
||`(0.65)`|`(0.91)`|`(0.42)`|`(0.68)`|
|`Lampung`|`-0.189`|`-0.285`|`-0.185`|`-0.275`|
||`(1.83)`|`(2.57)*`|`(1.80)`|`(2.49)*`|
|`West Java`|`-0.001`|`-0.043`|`0.022`|`-0.019`|
||`(0.01)`|`(0.63)`|`(0.34)`|`(0.29)`|
|`Central Java`|`-0.053`|`-0.090`|`-0.045`|`-0.081`|
||`(0.74)`|`(1.21)`|`(0.62)`|`(1.09)`|
|`Di Yogyakarta`|<br>`-0.239`|<br>`-0.285`|<br>`-0.225`|<br>`-0.269`|
||`(2.69)**`|`(3.14)**`|`(2.52)*`|`(2.96)**`|
|`East Java`|`-0.092`|`-0.136`|`-0.078`|`-0.120`|
||`(1.27)`|`(1.83)`|`(1.08)`|`(1.63)`|
|`Bali`|`-0.004`|`-0.060`|`-0.015`|`-0.069`|
||`(0.05)`|`(0.69)`|`(0.18)`|`(0.79)`|
|`West NusaTenggara`|<br>`-0.062`|<br>`-0.097`|<br>`-0.077`|<br>`-0.110`|

36
-7-

L. Income Statement Adjustment Five items, in particular, must be given special attention with regard to appropriate measurement under inflation. These are depreciation allowances, interest expenses, inventory valuation, capital gains/losses aid exchange gains/losses. This section considers the full indexation ef the items on the income statement where the appropriate form of indexation is discussed for each of the above items. In later sections we consider balr..ce sheet adjustments and the implications of various partial and approximate lndexation measures.

Under a tax regime where a flat rate tax is imposed on corporate income and depreciation allowances and interest deductions are allowed, neutrality requires that depreciation allowances be adjusted for inflation and not be based on historic cost. As far as interest deductions are concerned, only real interest expenses should be deductible and consequently the nominal interest rate has to be adjusted for the inflation rate. Since the nominal interest rate under inflation includes a component to compensate the lender for the anticipated decline in the real value of principal, an equivalent way to treat interest expenses is to allow nominal interest deduction but include the decline in real value of debt in taxable Income of the borrower. In addit.on, the cost of goods s:2ld out of inventory, capital gains, and losses on foreign exchange debts need to be adjusted for inflation. The principles under,ying, such adjustment are discussed under the appropriate headings below.

(a). Depreciation Deduction: All depreciation deduction schemes are attempts to approximate the unrealized change in the market value of a firm's assets. This section illustrates how the nominal value of depreciation deductions may be adjusted so that the real value is
level), down from 9.7 percent of GDP in 1989. In 1990, then, 1.4 percent of GDP was saved on pensions in addition to the fall in GDP. In 1991 GDP continued to decline, but 1989 retirees still managed to obtain 12.5 percent of 1991 GDP, a jump of 2.8 points compared with 1989 and 4.2 points compared with 1990.

Line 3 shows that giving the 1989 retirees the same real (that is consumer-price-deflated) pension that they earned in 1989 would have required 12.9 percent of GDP in 1991 (line 3). This amount is 0.4 percentage points more than the 12.5 that they actually received (line 2). Pensioners thus participated little in the 1991 general income decline. They participated less than proportionately, since the share of GDP going to 1989 pensioners rose.

Another way to look at pensioners' relative income gains and losses is to compare real pensions and real wages. This is done in table 5, but without distinguishing the 1989 pensioners Table 5: Net Real Wages and Pensions

||19881<br>Per<br>|1989<br>centage<br>|1 9901<br>of 1989, g<br><br>|1991 1<br>roup spe<br> <br>|1992 1<br>cific consu<br>|1993 1<br>mption in<br> <br>|1994<br>dex<br>|
|---|---|---|---|---|---|---|---|
|a. ZUS real pensions|99.0|100I|<br>84.9 ||<br>97.2|90.9 ||<br>90.3|92.9|
|b. Average monthly wage|91.7|100|75.6|75.4|73.4|71.2|71.6|
||||Percent|age of mo|nthly wag|e||
|**c. Relative monthly pension**|**51.2**|**50.6**|**56.8**<br>|**65.3**<br>|**62.7**|**62.1**|**64.0**|
|**d.**Relative monthly retirement|57.3|53.2|65.0j|<br>76.2|72.5|72.8|73.9|
|<br>|Per<br>|centage<br>|<br>of worke<br>|<br>r's house<br> <br>|hold per ca<br> <br>|pita spen<br> <br>|ding<br>|
|e. Pensioners relative spending|100|89|99 ||<br>105 ||<br>103 ||<br>113|113|
|<br>|||<br>G<br>|<br> <br>ini coeffi<br> <br>|<br> <br>cient<br>|<br> <br>||
|**f. Pension inequality**|**0.16**|**0.19**|**0.21 |**|<br>**0.25**|**0.26 |**|<br>**0.21**|||

-- not available

- a: Rocznik 1994, p.228, tab.5. own cumulation, does not include farmers.

b: Rocznik 1994, p.212, tab.4, own cumulation.

- c: 1990-93:Rocznik 1994, p.226, tab.3., 1989 own extrapolation.

- 1992-93: gross to gross instead of net to net.

- d: Rocznik 1991, p.238; 1994, p.227 and lxviii.

- e: GUS Bulletin, table I, various issues (new definition of pensioners since 1993).

f: computed on an "Excel" spreadsheet from brackets given in Rocznik (for example 1994, p.230. tab.8), using the middle of the bracket as the average income in this bracket.

from later entrants. In 1990 and 1991 pensions grew relative to wages and in 1992 the reverse happened (line c, table 5). In 1993 both followed a smilar path. In 1994 the pension base went up 17