rafmacalaba/data-use-mentions-extended huggingface dataset:
Proxy 3 definition of informal employment in 2016, new questions were also added to the questionnaire. In particular, book-keeping practices, types of benefits received from their employer, whether they have an employment contract, and the type of contract they have were all asked about. Additionally, the 2021 questionnaire asked respondents about whether, and when, the company or business in which they worked had been registered. Altogether, these changes imply that estimates of informal employment based on the SAKERNAS are not comparable over time, particularly for the pre-2016 and post-2016 periods. It is also unclear how the new question on registration status will affect estimates' comparability before and after 2021.

Given its comprehensive coverage of the population and the addition of new questions from 2016 onwards, SAKERNAS provides the most accurate estimates of informal employment among existing data sources. However, it also suffers from limitations. For example, information about main and secondary jobs is quite limited (Dong, 2016). This issue has been partly addressed by adding questions related to social insurance, employment benefits, and contract type, although these are only collected from employees. Consequently, data on employers, own-account workers, casual workers, and unpaid family workers remain unavailable, despite accounting for two-thirds of jobs in Indonesia (Wihardja & Cunningham, 2021). In addition, there is a wide range of jobrelated characteristics (e.g., work environment, nature of tasks, job satisfaction) that SAKERNAS does not capture. This hinders a comprehensive analysis of job quality in Indonesia. Finally, SAKERNAS was not designed to be a longitudinal survey. While a panel of households can theoretically be constructed from the rotating panel design, the period covered would be relatively short and not representative of the Indonesian population. Thus, surveys such as the Indonesian Family Life Survey, are needed to complement SAKERNAS.

_Indonesian Family Life Survey_ The Indonesian Family Life Survey (IFLS) is a multi-topic, longitudinal survey that was first conducted in 1993 by RAND Corporation alongside a number of Indonesian organizations. The
These results suggest that given the size of the multiplier associated with spending increases over the last two decades, a large fiscal adjustment through spending cuts could be more harmful to the economy than tax-based fiscal adjustment.

# **4 Conclusion**

In this paper, I use quarterly data from 1970 to 2010 to study the impact of government spending and net tax revenue shocks on key Canadian macroeconomic variables, employing sign restrictions as an identification strategy. I explicitly control for spillovers from the U.S. economy and for world oil price fluctuations. In addition, I examine the impact of fiscal shocks over two sub-periods: before and after the fourth quarter of 1990.

This paper has several key findings. The estimated value of both spending and tax multipliers is sensitive to the inclusion of relative oil prices and U.S. GDP in the VAR model. Output, consumption and investment decline as a response to an increase in net taxes. Output and private consumption increase when government purchases increase, whereas private investment falls. Net exports decline in response to both spending and net tax increases (with a short delay for the decline in response to the net tax increase) as a result of real exchange rate appreciation. Tax-cut multipliers vary between $0.20 and $0.50, while spending multipliers range between $0.20 and $1.10. Spending multipliers tend to be particularly larger than tax-cut multipliers over the last two decades.

The composition of government spending is relevant for the size of the multipliers. For example, some theoretical and empirical findings suggest that government investment tends to have larger GDP multipliers. Since these issues are not addressed in this paper, they are left for future research.

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of households can be followed for all five quarters.

We form pseudo-panels based on the household head’s year of birth and education level. Cohorts are defined by the interaction of five year birth intervals and three education levels (primary schooling or less, 7 to 12 years education, and more than 12 years education). For example, all household heads born

> 6 Since the second quarter of 2001, the ENEU was replaced by the ENE, which has now become the ENET - a national quarterly employment survey.

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as the proxy for expected net gain in absolute terms. When ∆ _yi_ is included as a regressor in the vector **x** _i_ , one potentially faces the problem of a contaminated regressor. The applicable explanatory variable is expected net gain while the variable used is a noisy realization of it. We are thus facing a problem analogous to the one of errors in variables in a linear regression model. The extent of the estimation bias induced by this problem depends of course on how accurate individual expectations are. If individuals can perfectly predict the actual income change, the use of ∆ _yi_ as explanatory variable is valid. The wider realized gains are distributed around expected gains, the more severe the bias introduced by using ∆ _yi_ .

There is yet another reason for why ∆ _yi_ is only a noisy measure of the expected income change. Individual shocks may not be i.i.d. in each month, but rather be correlated. For example, if a fisherman falls unexpectedly sick for an extended period of time right after purchasing a fibre boat and this reduces his ability to go fishing, ∆ _yi_ underestimates his expected gains.

For both of these reasons, we will experiment with two specifications in the empirical analysis. One where ∆ _yi_ is included in the **x** _i_ vector without modification and one where, in the spirit of the two stage least squares model, ∆ _yi_ is first regressed on a vector of instruments and its predicted values ∆<sup>�</sup> _yi_ say, are used instead. Indirect evidence for the “noisiness” of ∆ _yi_ is provided by the fact that our estimates of ∆ _yi_ are negative for one fifth of those households for which both catamaran and fibre sales data are available. For these households, individual rationality seems to be violated as they adopt although they expect smaller profits from the new technology.

To give an idea of how income change and adoption time are empirically related, Figure 2 plots _t_<sup>_∗_
>0.202<br>0.677_∗_<br>0.056<br>0.609<br>[0.787]<br>[0.366]<br>[0.805]<br>[0.384]<br>Observations<br>153,860<br>153,860<br>153,860<br>153,860<br>Mean DV<br>0.85<br>0.027<br>0.85<br>0.027<br>District FEs<br>Yes<br>Yes<br>Yes<br>Yes<br>Year FEs<br>Yes<br>Yes<br>Yes<br>Yes<br>Age FEs<br>Yes<br>Yes<br>Yes<br>Yes<br>_Source_: Author’s analysis based on NSS 2004 – 2010 (Rounds 61, 64, and 66) and program expenditure data for<br>SGRY from 2004 to 2007. Expenditure data is from the Ministry of Rural Development, Government of India.<br>_Notes_: All estimates are of the order 10_−_2. This table reports estimates of _β_, the effect of NREGA on children<br>who report their “primary activity” as school attendance or work. The coeffcients are from the OLS estimation of<br>equation5. The dependent variable in columns 1 and 3 is a dummy if primary activity of the individual is “attends<br>school”. The dependent variable in columns 2 and 4 is a dummy if primary activity of the individual is any kind of<br>work. Other controls include district fxed effects, year fxed effects, and a vector of year-child-age fxed effects.<br>The standard errors in square brackets are clustered at the district level. All regressions include district, year, age,<br>
performance oriented management, if properly implemented, would facilitate the identification of objectives and, consequently the efficiency of the company. This is particularly the case for SOEs where because of the lack of private investors, incentives for performance are difficult to create.

Together with the levels of professional management, the performance-orientation of SOEs is one of the aspects where SOEs in LAC show the largest deficiencies. This applies not only to the poor focus on external accountability but also to the lack of performance-orientation of the enterprise, especially in the evaluation of its staff.

Our measure of professional management finds three SOEs (CAGECE and Grupo CEEE from Brazil and AySA from Argentina) among the top state corporations of the region in terms of the quality of its bureaucracy. Paraguay’s ANDE is one of the few companies with performancebased schemes (although our measure does not reflect actual levels of implementation).

<!-- Start of picture text --> Performance Based PERFORMANCE ORIENTATION<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>T1 T2 T3<br>Source: LAC SOEs Governance Database, The World Bank, 2009. THRESHOLD LEVELS<br>NUMBER OF COMPANIES<br>1<br>.8<br>.6<br>.4<br>.2<br>0<br>T1 PAR JAM T2 COL MEX URU BZL D R PER T T ECU C R ARG BOL<br><!-- End of picture text -->

# **6. IMPACT OF CORPORATE GOVERNANCE ON PERFORMANCE**

This section explores the correlations between various dimensions of corporate governance and the operational performance of utilities in the water and electricity distribution sectors of LAC. We correlated the dimensions described in the previous sections with the level and growth rates of the main performance indicators for utilities in the water and electricity sectors. We ran the governance indicators
/sup> The systematic land registration/titling component -which accounted for most of LARP spending- aimed to issue 90-year leases essentially free of charge to some 55,000 land plots from informal settlements in urban and peri-urban areas of Maseru, a city of some 300,000 inhabitants. The remainder of program resources was devoted to a subcomponent supporting legal and institutional reforms to enhance effectiveness and efficiency of land service delivery to reduce the cost of registering land transfers and mortgages and to improve women’s access to land rights through passage of a new Land Act and associated regulations as well as establishment of a new Land Administration Authority (LAA) in 2010.

> 3 Data from the registering property section of the World Bank’s ‘Doing Business’ indicators shows that registering a land transfer in Africa (a lower bound for first time registration) still costs close to 8% of land value, a figure that changed somewhat since 2005 (Deininger _et al._ 2020a). 4 Applicant characteristics such as having a stable income as well as the benefit stream from the proposed use of borrowed funds will be the main factors affecting whether or not they will receive a loan. However, if there is a non-zero risk of default, a lender’s willingness to lend funds to applications will be affected by _pV_ - _f_ where _V_ is the value of land owned, _f_ a fixed foreclosure cost _f_ , and _p_ the likelihood of finding a buyer. 5 To avoid confusion between first and second registration, we refer to first registration (either sporadic or systematic) as ‘titling’ or ‘issuance of a title/lease’. The subject(s) of this transaction are referred to as ‘owners’ although technically they are leaseholder(s).

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of a rural household. Failing to adjust by cost-of-living differences would over-estimate poverty in rural areas, and under-estimate them in urban areas.

International poverty rates in the region in most cases are based on welfare aggregates that are not spatially deflated. While all South Asian countries carry out spatial deflation when calculating their national poverty estimates, the World Bank currently only spatially deflates the welfare measures in Nepal and Bhutan when calculating international extreme poverty rates. Bhutan uses a survey-based price index (S-SPI) to deflate prices. In this case, the spatial price indices are derived using information derived from the survey. Similarly, Bangladesh and Nepal use the Implicit Spatial Price Index (I-SPI) to deflate prices. The implicit spatial price index is constructed using regional specific poverty lines to determine the cost-of-living differences (Deaton and Muellbauer, 1980).<sup>14</sup> Table 7 shows the international poverty rates using the nominal and spatially deflated national consumption aggregates. Overall, the absence of spatial deflation in calculating the international extreme poverty rates seems might have a minor effect on the estimation of country-level international poverty rates, but it can have substantial impacts on international poverty measurement across regions within countries. In most countries, except for Nepal, the impact of spatial deflation is non-trivial. Without spatial deflation, urban areas have less poverty, and rural areas have more poverty **_._** For example, in Nepal, if the consumption aggregates were not spatially deflated, then urban international extreme poverty rate would be 4.3 percentage points higher and rural poverty would be 7.1 percentage points lower. If Bangladesh spatially deflated its consumption aggregates, then it would see urban international extreme poverty rate 3.3 percentage points higher and rural extreme international poverty rate 4.7 percentage points lower.

**Table 7. International extreme poverty rate in urban and rural areas,** **<u>with and without spatial deflation</u>**

||**Inter**<br>*
3 Sixth, several MENA countries have introduced special interventions to induce banks to lend more to SMEs. In addition to the use of state banks, special programs have included exemptions on reserve requirements, credit subsidies and partial credit guarantee schemes. Guarantee schemes have proved particularly popular and are in operation in ten MENA countries. The paper provides some evidence that these schemes have contributed to more SME lending, although it is difficult to evaluate the extent to which these schemes are cost-effective.

While state banks and other interventions such as guarantee schemes may have a played an important role in providing finance to SMEs in an environment where financial infrastructure remains weak, the results also allow for the identification of MENA‟s policy agenda in the area of SME finance. Strengthening credit information systems and creditor rights should remain the priority item in the legal/regulatory agenda. Credit guarantee schemes may play an important role, but it is essential to ensure that these schemes are well-designed and cost-effective. Finally, avoiding overly restrictive entry requirements and allowing the entry of international and regional banks showing leadership in SME finance can improve competition and produce positive direct and indirect effects in the market for SME lending.

The rest of the paper is structured as follows. The second section provides an overview of the two previous SME banking surveys and their main results. The third section reviews how the MENA survey was designed and implemented. The fourth section discusses the overall survey results. This includes the actual and target bank lending to SMEs, the main strategic approaches adopted by MENA banks in dealing with SMEs, the main products offered, and the risk management techniques employed. The fifth section presents a preliminary econometric analysis of the dataset built from the survey results and other sources. Finally, the sixth section concludes and identifies the key policy implications.

# **2.  Overview of Previous Surveys**

As mentioned before, two World Bank surveys were conducted in recent years as part of an effort to investigate the status of bank lending to SMEs. These surveys share some important
the other hand, rainfall has no impact on migration to non-India destinations. The estimated effects are small and statistically insignificant.

Since I have only three periods, arbitrary trends in normalized rainfall could be driving the results. Indeed, Table 3 and Figure 5 shows that normalized rainfall in the past year has been falling between 2001 and 2010, whereas migration rates have been increasing over this period. To check that the trend in rainfall is not driving my results, I extend the panel further back in time using district level migration rates from the census of 1981 and 1991 to proxy for the migration rates in the village in 1981 and 1991. Table 5 shows the results for this extended panel. The same specification produces almost identical results except for effects on India migration from urban areas (columns 1, 3, and 5). The effect for the urban areas is about half the size of the effect for rural areas. This could be because urban areas are less reliant on rainfall for their income<sup>17</sup> or, according to the theoretical framework, because the fraction of households affected by the liquidity constraint is smaller in urban areas. Adding a linear time trend only slightly reduces the point estimates. This indicates that time trends in rainfall are not driving the results.

In Table 6, I investigate whether rainfall shocks two years before the survey affects migration rates. I do this to capture the effect on migrants who left more than a year ago for whom it is not the last year’s rainfall but the rainfall two years ago, that matters. Baseline estimation of Equation (1) shows that normalized rainfall two years ago matters almost as much as the normalized rainfall last year for migration to India (columns 1, 3, and 5). But this relationship is

> 17Only 45 percent of urban households owns agricultural land compared to 87 percent of rural households.

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the normalized cells of our type-by-type matrix _π_ that captures the total number of links between all types. We normalise the rows of _π_ by dividing each entry in a row by the sum of that row. We abstract from any endogenous network adjustments (see e.g. Panigrahi, 2022; Eaton et al., 2022; Arkolakis et al., 2023). We assume that _υjt_ is an independent draw from a uniform distribution _U_ [ _−_ 10 _,_ 10] for every type _j_ in every time period _t_ . Each type starts with a randomly chosen output drawn from the distribution _U_ [0 _,_ 100] in _t_ = 0.

Using this set-up, we first simulate the output process without any shock. Then, we simulate the output process following a negative output shock to sector-region-size type _j_ ’s value added _υjt_ in the first time period.<sup>29</sup> We repeat this exercise for all types _j_ .

To study the relevance of unobserved informal firms, we conduct our simulation exercise twice. In the first scenario, we use the matrix _π_ derived from administrative records. In the second scenario, we use an alternative version of _π_ using our revised network that accounts for the presence of informal firms.<sup>30</sup> Our primary question is: how do domestic shocks impact each type when informal firms are considered versus when they are not? For each simulated shock, we compute: (i) the absolute reduction in output of each type using the original adjacency matrix (excluding informal firms) and (ii) the absolute reduction in output of each type using the new adjacency matrix (including informal firms), both averaged across all time periods. This yields a matrix of shock impacts where each row corresponds to a supplier who is shocked and each column corresponds to a buyer who faces the impact of the shock. We then aggregate across rows to compute the average impact of the shocks on buyers.

We find that
road density|km/1000 km<sup>2</sup>of arable land|86.6|**158.1**|507.4|
|Unpaved road density|km/1000 km<sup>2</sup>of arable land|504.7|**804.0**|1,038.3|
|GIS rural accessibility|% of rural population within 2 km of all-season road|21.7|**24.0**|59.9|
|Paved road traffic|Average annual daily traffic|1,049.6|**1,314**|2,786.0|
|Unpaved road traffic|Average annual daily traffic|62.6|**40.4**|12.0|
|Paved network condition|% in good or fair condition|80.0|**75.0**|79.0|
|Unpaved network condition|% in good or fair condition|57.6|**74.0**|58.3|
|Perceived transport quality|% firms identifying roads as major business constraint|23.0|**17.6**|10.7|

Source: Gwillliam and others 2009. Derived from AICD national database, downloadable from http://www.infrastructureafrica.org/aicd/tools/data

## **Challenges**

In recent years, the depreciation of the national currency has gradually eroded the real value of the fuel levy. Adjusting its value is essential if Ghana is to sustain its relatively good performance on road network preservation. The absolute value of the existing fuel levy is already relatively low by African standards—about half the levels found in Ethiopia, Kenya, and Tanzania—which suggests that a revision to preserve the real value of the levy should not be overly burdensome for the transportation sector.

10
assess the quality of regulation itself and the general context that determines how regulation functions. We construct this index using measures from the International Country Risk Guide, which evaluates a country’s risk for international investment by looking at its social and political situation. Specifically, we average the values of indicators measuring the absence of corruption in

> 14 Other studies, such as Nicoletti et al. (2000) or Klapper et al. (2004) also use factor analysis to decompose regulation measures, and they further replace the measures with their principal components in the regressions.  Because of the strong correlation between the components and our indices (see Table 2), we choose not to use the principal components in our regressions.

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over 1988-2010.

Our second step is to use the model estimates from 1988:Q1-2008:Q3 to generate out-ofsample predictions for trade policy responses during 2008:Q4-2010:Q4, given the macroeconomic shocks that arose during the Great Recession. The model predicts a surge in import protection for the United States and European Union in particular in 2009:Q3. In terms of trade values, back of the envelope calculations put the forecasted _new_ TTB import protection during 2008:Q4-2010:Q4 as

> 1 A reasonable question is the extent to which our singular focus on TTB policies fully captures the new import protection activity during 2008-2010 by the five economies in our sample. According to data from the Global Trade Alert, TTBs are by far the predominant trade policy instruments through which these economies directly erected new import-restricting trade barriers in 2008-2010. Appendix Table I lists the _only other_ examples from these economies that the Global Trade Alert characterizes as “red” – i.e., the measure has been implemented and almost certainly discriminates against foreign commercial interests - and is directed at imports. From this list, it appears that only a South Korean increase in tariffs on 16 different products in January 2009 would be characterized as a substantial protectionist import restriction that is not captured by our focus on TTBs.

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private cost increases with the level of VTE, up to 94% in the case of post-secondary VTE. The total private cost of the latter is more than twice that of secondary VTE.

The cost figures for apprentices are approximate, because many apprentices receive room and board, the value of which should be subtracted from foregone wages. On the other hand, some apprentices have to pay a fee. Unfortunately, we have no direct data on the value of room and board, nor on the amount of the fee. Since the apprentices who pay fees are fewer than those who receive room and board, on balance the calculated opportunity cost is likely to be an overestimate. We shall return to this problem when we perform a sensitivity analysis on the cost calculations.

# Institutional Costs

The calculation of institutional costs for the VTE system in C8te d'Ivoire was a fairly demanding exercise, mainly because of the complex structure of the system (see section 3) to which is added an even more complex system of budget administration. In particular, major cost components, such as the salaries and benefits of expatriate staff, the housing allowances of Ivorian staff, and certain scholarships are not managed by the Ministry of Vocational and Technical Education or by the relevant institute or school, and hence do not appear on their budgets. The calculations thus needed to rely on a variety of sources such as budget data from various ministries, institutes and schools, payroll data, direct