rafmacalaba/datause-encoder-data huggingface dataset:
who answers the questions. Household surveys in developing countries typically ask the head of the household, usually the male spouse, to answer employment questions about all household members.<sup>14</sup> Proxy respondents may not always provide accurate information, and this may bias the obtained statistics on employment and their distribution (Hussmanns, Mehran, and Verma, 1990). One alternative is to ask individual household members above a certain age directly; as do the Living Standards Measurement Study surveys (LSMS)<sup>15</sup> and Labor Force Surveys (LFS). However, requiring self–reporting from all individuals puts an extra logistical and financial burden on the fieldwork, and in practice survey managers often face a trade‐off between information accuracy and the cost to obtain it.<sup>16</sup> An experimental study for the US investigated the potential bias of proxy versus self‐response for health statistics, finding that randomly selected subjects reported fewer health events for themselves than for other household members (Mathiowetz and Groves 1985). In earlier analysis, we assess the implications of survey design for descriptive statistics and find important effects of proxy versus self‐reporting on resulting labor statistics in Tanzania, observing that reporting by proxy leads to lower male employment rates, mostly due to underreporting of agricultural activities (Bardasi et al 2011). This bias is reduced when the proxy respondent are spouses or have some schooling. The consequences of these observed differences in categorization for the estimates of structural parameters, such as the returns to education, remain, however, unknown.

# **3. Experimental design and estimation strategy**

Given the limited evidence of the effect of survey design choices on returns to education estimates, the survey experiment focused on the two key dimensions discussed above: (i) the level of detail of the questionnaire, more specifically the screening questions to establish employment status, and (ii) the type of respondent, namely self versus proxy response. Households were randomly selected and allocated to one of the four survey assignments based on these two dimensions. All household members aged 10 or above were eligible to respond to the individual‐level module on employment, and we consider all labor force participants to estimate the returns to education.

> 14 This is the approach followed by standard surveys like for instance Household Budget Surveys (HBS), Household Income/Consumption Expenditure Surveys (HICES) and Core Welfare Indicator Questionnaires (CWIQ) among others.

> 15 See Grosh, and Glewwe (2000)

> 16 Interviewing only self‐respondents may require many re‐visits, which can be costly.   Response by proxy rather than individuals themselves reflects the common practice to interview an informed household member (often the household head or spouse), rather than each individual him or herself. In practice proxy respondents are often used when individuals are away from the household or otherwise unavailable in the time allotted in an enumeration area to conduct interviews.

8
Table 1: **Calibration**

||Values|Target|
|---|---|---|
|Risk aversion|_σ_ = 2|Arellano (2008)|
|Output cost after default|_γ_ = 0_._96|Arellano (2008)|
|Risk free interest rate|1.7 %|Arellano (2008)|
|Core’s income process|_ρ_= 0_._96, _σε_ = 0_._003|Data|
|Periphery’s income process|_ρ_= 0_._92, _σε_ = 0_._004|Data|
|Output diference| ̄_yc/_ ̄_yp_ = 1_._2|Data|
|Core’s borrowing limit|66%|Treaty|
|Periphery’s borrowing limit|83%|Treaty|
|Calibrated parameters|||
|Core’s discount factor|_βc_ = 0_._89|0.6% spread|
|Periphery’s discount factor|_βp_ = 0_._88|2.4% spread|

Table 2: **Business Cycle Statistics: The Benchmark Model and the Data**

|||**Data**|**Ben**|**chmark**|
|---|---|---|---|---|
|_mean(%)_|Core|Periphery|Core|Periphery|
|Debt/Y|66|83|66|79|
|Spread|0.6|2.4|0.5|1.9|
|C/Y|77|80|98.8|98.6|
|_std(%)_|||||
|Debt/Y|8.10|19|0.16|0.36|
|Interest rate|0.9|2.16|0.019|0.042|
|C/Y|1.15|1.9|0.14|0.15|

# **3.2 Results**

This section first analyzes the policy functions of the benchmark and the Eurobonds models and then examines the quantitative performance of the Eurobonds model in comparison with the benchmark model.

The introduction of joint-liability bonds generates two opposing forces. On the one hand, this instrument generates a contagion effect, in the sense that it may push some countries to default even though they are individually solvent. On the other hand, joint-liability bonds may create cheaper access to credit, since insuring other countries allows for lower rates.

Figure 2 shows the effects of introducing Eurobonds and having cheaper access to the financial markets for the Core countries. It compares the spread that is generated by the benchmark and 12
by higher security to prevent terrorism. Our results appear to be perfectly consistent with these two views. We have found that the negative impact of terrorism is two to three times higher for products that have these characteristics. Further, using an additional dataset from the department on state on visa issuance from 1997 to 2002, we have shown how terrorism affects the number of business visas delivered by the US, thereby impacting significantly bilateral exports in differentiated products. All these results suggest that security to prevent terrorism does matter for US imports.

What can we conclude from these results? As long as US imports come mainly from countries that do not represent a high risk in terms of terrorism acts, the US consumers should not be too much affected by security measures at the borders. However, those few countries at the origin of most of the attacks towards the US could be highly affected, especially those countries for which the US often constitutes a significant market for their export products. Hence, the protection of US lives might be undertaken at the expense of some foreign less developed countries’ economies. Our results are consistent with the role played by security measures at the borders. It should be noted however that other elements might as well affect the nexus between trade and transnational terrorism. For instance, changes in the behaviors of insurers (higher rates of insurance prices) or changes in consumer choices (discrimination and embargo) could also affect trade and consequently terrorist attacks.

Besides, we assign in this paper each terrorist attack to one particular origin. We know however that this is only partly true in today’s changing forms of terrorism where terrorist organizations are increasingly becoming more multinational. Put differently, this paper does not study the indirect impact of terrorism from one country of origin on security measures over other suspected countries, which for instance might host groups from the same ’multinational’ organization. One might argue that the indirect impact can be substantial as well. All these issues that arise naturally from our work, deserve to be specifically investigated in future research.

25
poverty imputation methods (and the associated roadmap pointing to the relevant discussion in this paper), Table 1 offers another classification that is more technical and data-oriented.

Table 1 also lists the typical poverty imputation (or corresponding data) situation, examples of surveys, and some recent studies corresponding to each missing data category. In particular, Category A can be further broken down into two data situations: one where the available survey produces no consumption data, and the other where the available survey is designed for project targeting purposes. Corresponding to these data situations are the Demographic Health Surveys (DHS) and most small-scale surveys. Category B can also be further disaggregated into three different but related data situations: consumption data are incomparable across survey rounds, consumption data are unavailable in the current survey but available in some other related surveys, and consumption data are unavailable at more disaggregated administrative levels than those offered in the current survey. Finally, Category C addresses the widespread situation that most surveys in developing countries do not provide (nationally representative) household panel data. Table 1 also offers some recent studies that we will discuss in more detail in later sections.

# **I.2. Typical Estimation Equations**

While we focus in this paper on the intuition behind existing studies, it can be useful to briefly discuss the commonly used empirical framework for clarity. Let _xj_ be a vector of characteristics that represent all the factors that determine a household’s consumption, where _j_ indicates the survey type. More generally, _j_ can indicate either another round of the same household expenditure survey, or a different survey (census), for _j_ = 1, 2.<sup>3</sup> Subject to data availability, _xj_ can include household variables such as the household head’s age, sex, education, ethnicity, religion, language

> 3 More generally, _j_ can indicate any type of relevant surveys that collect household data sufficiently relevant for imputation purposes such as labor force surveys or demographic and health surveys..

6
**Figure 8: Location of commercial teff farms in 2003/4 with smallholder kebeles and their yields in 0-25, 25-50, 50-100, and 100-150 km distance bands**

<!-- Start of picture text --> Legend<br>Kebele boundary 2004<br>Yield (q/ha) by quintile<br>0 - 3<br>4 - 5<br>6 - 7<br>8 - 9<br>10 - 17<br>Region boundary<br>Buffer around Teff farm (04)<br>Distance (km)<br>25<br>50<br>100<br>150<br><!-- End of picture text --> 33
**Poly,Pnnirg,** and **Ro"arch**

# **World Dev3lhpment Report|**

The theoretical basis for the "heterodox shocks" recently implemented in Argentina and Brazil is that chronic inflation is essentially inertial - the product of staggered prices and wage adjustments. The underlying assumpton is that the economic process is a cooperative game. Without legal and other forms of coercion, however, individuals tend to cheat - to fix their prices above average to start with.

The inertial hypothesis of inflation is a good description of the dynamics of inflation but it is _not_ a theory of the nature of inflation - so the proposed remedy (the "heterodox shock") cannot be implemented successfully.

Moreover, applying that kind of shock destroys the spontaneous operation of the price system by suppressing the information content conveyed by prices and by distorting the allocation of resources.

Once a government engages in such an experiment, it is led to repeat it periodically to survive. The countries that entered this path are likely to remain for a long time under a controlled economy, sacrificing their growth potential on behalf of some stability in income distribution and less explosive inflation.

Eventually this "muddling through" policy may break down, precipitating hyperinflation and consequent structural changes - but this does not seem to be an imminent or even a necessary outcome.

A basic flaw of the "heterodox" stabilization programs was to assume that stabilizing the price level (through a general freeze) was a precondition for fiscal equilibrium and eventual fiscal reform - instead of the reverse. The fiscal austerity eromised after stabilization was never - accomplished blocked by bureaucrats and special interest groups interested in maintaining the status quo. The challenge in these countries is to devise economic programs that could make long-term stabilization programs viable and politically acceptable.

In this sense, stabilization is less a technical economic problem than an intertemporal political problem of how to compensate the losers, on the one hand, and on the other hand to convince the majority that the trade-off between sacrificed current consumption and increased future consumption is worthwhile. The precarious political systems in these countries have been unable to deal with conflicts and support consistent long-term policies.

This paper is a background paper for the 1988 World Development Report. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Lupita Mattheisen, room S13-067, extension 33757 (36 pages with charts and tables).

The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research i Complex. An objective of the series is to get these fmdings out quickly, even if presentations are less than fully polished. The findings, interpretations, and zonclusions in these papers do not necessarily represent official policy of the Bank.

i Produced at the PPR Dissemination Center
Eq. (11) captures the distortions in input choice relative to the optimal combination of factor input. More specifically, it states that a firm faces a high capital distortion (larger _τk_ ) when the ratio of labor to capital compensation is high compared to the efficient allocation of input. It is worth emphasizing that _τk_ measures capital market distortion relative to labor market distortion. Thus high capital distortion (larger _τk_ ) should be interpreted as a low labor distortions, and vice versa. Eq. (12) states that a firm faces a high ‘output’ distortion (higher _τy_ ) when the labor compensation of the firm is low compared to what one would expect in a frictionless environment.

The establishment-level productivity can be inferred as: <u>1</u> where _κ_ = ( _PsYs_ )<sup>_−_</sup> _σ−_ 1 _/Ps_ , which is normalized to 1, as in HK.

It is worth emphasizing that the HK framework allows to obtain physical output _Y_ using the CES demand relationship.

<u>1</u> The industry TFP would be _A_<sup> ̄</sup> _s_ = _Mi_ =1 _s_<sup>_A_</sup> _si_<sup>_σ−_1</sup> _σ−_ 1 , if marginal products were equalized across �� � establishments within industry. HK show that the ratio of the actual TFP in 9 to the efficient level of TFP<sup>7</sup> : Eq. 13 shows how within industry misallocation of resources leads to a lower measured TFP.

# **5 Data Description**

Our analysis exploits census data for manufacturing firms in each of the four SSA countries we study: Cˆote d’Ivoire (2003-2012), Ethiopia (2011), Ghana (2003), and Kenya (2010). These countries provide comprehensive and comparable census data. The censuses are nationally representative and both small and large firms in the formal sector are adequately included in all countries. In all four countries, the data are restricted to manufacturing sector (ISIC Rev 3 15-37).

In what follows, we describe each country’s datasets.

**Cˆote d’Ivoire** The data source for Cˆote d’Ivoire is balance sheets and income statements associated with tax reporting. The data is available for all registered firms in the country and contains detailed balance sheet information on firms’ revenue, employment, cost of labor, book value of fixed assets, intermediate inputs and other firm characteristics. All registered firms are required to report their financial statements to the National Statistics Institute (INS), the tax administration (DGI), the court of justice, and the Central Bank (BCEAO), which are reported under the West Africa accounting system standards, Systeme Comptable Ouest Africain (SYSCOA). INS processed the data after firms hand in hard copies of their forms between March and June following the closing of the fiscal year in December. The Cˆote d’Ivoire data cover 2003 to 2012.

> 7Following Hsieh and Klenow (2009), we use an establishment’s total wage bill (including benefits) instead of employment in order to account for differences in the quality of labor across establishments.

12
second, the incidence of hunger; third, the low coverage rate of targeted health subsidies; and fourth, geographical aspects of poverty in the city. Table 3 includes a few sample tabulations of these latter variables for illustrative purposes.<sup>13</sup> <u>Labor Market. The survey provided ample information on the link between the labor</u> market and poverty in the city. Unemployment rates of the poorest income group were found to be around 40 percent; the working age population of whole _barrios_ in the poorest parts of town was forced to be idle and youth unemployment was at exorbitant levels. For the large majority of the poorest income groups, employment was only available in informal jobs, defined here as those without formal contracts and/or without access to social security. More than 70 percent of the employed population of the poorest income group were without formal employment contracts and only 13 percent of them had access to social security. Breakdowns of the pattern of unemployment revealed that it impacted somewhat more on men than women; that it was especially a phenomenon of the young; and that it was, surprisingly, especially those young people with a completed secondary and incomplete university education that were at the highest risk of becoming unemployed. This pointed to an important mismatch between the contents and quality of secondary education and the skill demands of the labor market.

Since the survey collected quite detailed data on hourly earnings of those employed, it did allow us to estimate earnings equations to assess segmentation of the labor market and rates of returns to schooling.<sup>14</sup> We found that, all factors held equal (like experience and years of education), a significant gender discrimination existed with women earning 17 percent less than equally qualified, educated and experienced men. Further, an ‘area’ effect played an important role in wage formation as workers from the wealthiest districts in the city were able to earn a 30 percent premium compared to workers living in the other, poorer parts of town. This was possibly attributable to a stigma or social class effect – or it might have also reflected differences in the quality of education across town. We found that primary schooling had a comparatively good return with every year of primary schooling increasing expected earnings by about 9 percent. But private returns to secondary schooling were considerably lower (at 6.5 percent), supporting the link between unemployment and

> 12 In dividing total household income by household size, we assumed that no economies of scale in consumption exist. Testing for variation in the household economies of scale did not produce significant shifts in the poverty profile (see Lanjouw and Ravallion 1995 for a discussion).

> 13 For a complete discussion of the Cali poverty profile, see  World Bank (2002).

> 14 We estimated a Minceranian equation in which the log of hourly wages was regressed against individual and household characteristics (like education, age, gender, type of occupation, area of residence etc.).

12
_5_ of GDP which imply a much lower return to education. One extra year of education of the workforce will, it is suggested, raise GDP by 9% for the first three years of education, falling to 4% for further years of schooling. If the social return ca.. lated from earnings data is 20% and the share of labor in the national product is 75%, then an extra year of education for the whole workforce should raise GDP by around 15%3. If the figure of 4-9% is believed to be consistent with the microeconomic results, it implies that the main benefit of education is simply to give people an advantage in a close to zero sum game. But it is, on balance, unlikely that the main effect of education is to allow the educated to gain at the expense of the uneducated; more probably the high survey-hased estimates of social rates of return should be treated with caution. There are a number of reasons for this.

Table **1** Selected Studies of the Return to Education Calculated from Survey Data Behrman and Birdsall (1983) Rates of return in Brazil. Study takes account of quality 6171 males from as well 1970 Census. of education. Psacharopoulos (1985) Survey of rates of return Summary of 105 country studies. 55 were developing countries. The estimates are calculated from cross-section data. Private and social rates of return shown. Social rates of return do not include any external effects.

Glewwe (1991) Rates of return in Ghana 3200 Study assesses return to households in 1988-89 survey. schooling separately to literacy Results on 1586 households and numeracy. used in this study.

First of all, there is the possibility that, when estimates of the return are based on cross-sectional analyses, then the estimates are likely to reflect in part high scarcity returns to a few more educated individuals. According to Behrman (1990) this is unlikely to persist over time. This MIbe calculation is not exact because, if the social rate of return to education is 20%, the effect on adult wages of an extra year of education will differ slightly. It will be higher because the cost of providing the education is reflected in the social cost, but lower because child wages may be below adult wages. Not too much weight should be placed on the second point because, in developing countries, people in their mid to late teens are often found in primary schools.
number of questions about corruption). This suggests that firms are distinguishing between “having to pay bribes” _per se_ which in an open ordered deal environment creates a predictable “tax” and policy uncertainty.

Another piece of evidence supports this conclusion. Firms in the Cote d’Ivoire, Kenya, Nigeria, and Senegal survey responded to whether ‘policy uncertainty’ was related to concerns about how existing laws and regulations would be applied to them as opposed to intertemporal changes in the laws themselves. Just over 60 percent agreed it was a moderate to severe constraint (similar to the rate given in figure 1). But even more tellingly, firms who report “knowing a bribe will get something done” is not a constraint, were less likely to see uncertainty in implementation as a constraint.

# **Table 6b:**

## **Concern about how formal policies will be applied in practice is widespread -- but less so if you see deals as not constraining**

|||**All firms**|**Of firms who rank 'knowing a bribe will**<br>**get something done' is not a constraint**|
|---|---|---|---|
|How large a constraint to the operation|No/Minor constraint|39.5%|52.3%|
|of your business is "uncertainty about|Moderate constraint|28.3%|26.6%|
|how official, formal policies will actually|Major/Severe|32.2%|21.1%|
|be applied to my business in practice"?|Total|494|104|
|Supplemental survey of firms in Cote d'Ivoire, Ken|ya, Nigeria and Senegal|||

# **_IV.   Impact of Deals_**

As a final step, we turn to examine the impact of uncertainty and the extent of deals on firm behavior. We look at firm employment decisions and employment growth over a three year time period. The focus is not whether or not a particular firm benefits from participating in a deal, but rather the effect of the ‘deals environment’ on firm 34