rafmacalaba/datause-encoder-data huggingface dataset:
# **TABLE 5. Firm performance after investment in ICT**

||F<br>|E<br>|FE‐<br>|2SLS<br>|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|**Panel A:****Labor P**|**roductivity**||||
|ICT|0.074***|0.070***|0.21***|0.20***|
||(0.019)|(0.019)|(0.064)|(0.064)|
|Observations|3,391|3,382|3,391|3,382|
|**Panel B:****Log Rev**|**enue**||||
|ICT|0.16***|0.089***|1.65***|1.59***|
||(0.025)|(0.019)|(0.38)|(0.40)|
|Observations|3,517|3,477|3,517|3,477|
|Industry effects|Yes|Yes|Yes|Yes|
|Trends||Yes||Yes|

Dependent variable: change in log value added per worker (Panel A) and change in log revenue (Panel B). Regressor: variable indicating whether firm invested in ICT during the sample period. Instrument: dummy indicating whether firm was exposed to information on government program to finance ICT investment interacted with firm‐size indicators at the beginning of the sample period. Columns (2) and (4) control for firm specific trends. Robust standard errors in parenthesis.

29
# **I. Introduction**

Informality has been drawing increasing attention from academics and policymakers alike because of its important implications for government revenues, firm performance and overall private sector development.

In this paper we use firm-level, cross-country data from Investment Climate (IC) surveys in 49 developing countries to investigate the relationship between informality – as proxied by firms’ self reported tax compliance – and an important correlate of productivity: access to credit and external finance.

There are many angles to the concept of informality. Informality is the product of firms, workers, or/ and tax payers who decide, voluntarily or not, if and to what extent to enter the formal sector (see World Bank, 2007). This choice occurs across multiple margins. For example, firms might choose not to register their activity and thus operate completely outside the formal system, or to register their business but evade, completely or partially, social security contributions or taxation. In this work, we focus on a direct, albeit partial, measure of informality: firms’ self reported tax compliance, which can be interpreted as a proxy for informality among otherwise formal (registered) firms.

When deciding how much to comply with taxation, firms trade off taxes outlays and “legality” on one side, against the possibility of retaining more profits at the risk of being found out and fined. A firm’s decision not to comply with tax and regulations can have important consequences at the aggregate level. Informality is said to likely decrease aggregate productivity by reducing average firm size. Informal firms also impose a negative externality on competitors because they can under-price their products, so that informal, less productive firms are more likely to survive. Finally, informality is said to affect firm productivity negatively (see World Bank, 2007).

Notwithstanding a wealth of anecdotal literature on the topic, rigorous evidence on the channels through which informality affects productivity is scant.<sup>2</sup> This paper sheds light on one of the potential mechanisms through which informality can affect productivity: lack of tax compliance limits the extent to which balance sheets are informative for banks’ lending and effectively restricts firms’ access to credit and to external finance.

Thanks to the richness of our data, we are able to relate firms’ self-reported tax compliance with a number of proxies for the extent of firms’ access to external finance. In

> 2 See, however, recent evidence in Fajnzylber et al. (2006), Kenyon (2006); and World Bank “Informality: Exit and Exclusion”, (2007);

2
17 most producers (94%) applied the recommendations provided by extensionists. Of those applying the recommendations, 19% reported a 100% effectiveness, 61% reported 50 to 75% effectiveness, and 20% reported 25% effectiveness. Two more measurements of value of extension are the evaluation of INTA's technical assistance (ATPb+ATPI) and the change in producers' income as a result of that advice. Of the sampled producers, 43% and 50% ranked the service as "very helpfur' and "helpfur', respectively. Forty one percent of the sampled producers reported an increase in their income, 47% reported stable income, and 12% reported a decline in income. These indicators, although not comprehensive in nature, provide some insight on the impact of INTA's technical assistance.

Although at this stage it is still impossible to distinguish between ATPb and ATP 1 producers in the ESECA (1997a) sample, some interesting hypotheses can be stated. Table 5 shows that of the sampled producers, 25% were contacted once a week, 50% were contacted every fifteen days, and the rest (25%) were contacted between every three weeks and every three months.<sup>10</sup> Under conditions in Nicaragua, producer contacts was dependent on the level of accessibility to the producers, especially after heavy reainstorms that wash away roads. Thirty two percent and 27% of the producers were not accessible all year round by car and by motorcycle, respectively.

Table 5: Number of visits by extension agents in the ATPb and ATP1 programs <!-- Start of picture text --> Frequency of visits (days) 7 15 |21 30 45 60 901<br>Share of population (%) 25 50 3 12 1 3 1<br>Source: ESECA, 1997a<br><!-- End of picture text -->

> **10** An interesting question is what characterizes the producers that are more frequently contacted. Additional finding is that 26% of the sampled producers paid for their extension services and 74% got it for free. Forms of delivery of recommendations are also split at the same rate. 29% received written recommendations, 68% received verbal recommendations, and 3% received recommendations in other forms. A hypothesis for verification is that those producers paying for the service were also visited once a week, and given written recommendations. Producers paying for the extension belong probably to the ATPI program. If this is true, then it would be easy to compare between the performance of the extension agents and the producers in the cofinanced program and in the traditional public extension program.
households receive significantly larger amounts as a proportion of their market income). The size of the benefit is also quite large compared to their income, totaling from 60 percent of market income for the bottom 10 percent to around 20 percent for households in the 50<sup>th</sup> percentile. The shares of education and health transfers tend to be large for poor households because their market income (i.e., the denominators used in the calculation of the share) is very low. At the same time, these households pay very little into the fiscal system.

Second, in fact most households do not pay much into the system. This is mainly because personal income taxes have a relatively high exemption threshold, and sales taxes apply only to a selected number of goods that are also more likely to be consumed by richer households. Both direct and indirect taxes represent a higher share of income for households in the top deciles, whereas their impact is small for most others. Households in the top 20 percent are net payers under Bhutan’s fiscal system, with most of the payment occurring through indirect taxes and only a modest amount through direct taxes. The incidence of indirect taxes falls predominantly on households in the top two deciles.

Third, due to the lack of direct transfers, the net cash position is negative for households across the board, though the magnitude is minimal for the bottom 40 percent of the income distribution. The net cash position measures all tax payments and cash benefits, while net benefits additionally consider indirect transfers.

Figure 5. Distributional impact of tax and benefit system in 2017 <!-- Start of picture text --> 80.00%<br>60.00%<br>40.00%<br>20.00%<br>0.00%<br>1 2 3 4 5 6 7 8 9 10<br>-20.00%<br>-40.00%<br>Direct Taxes Indirect Taxes Pension Contributions<br>Non-Pension Contributions Education Health<br>Net Benefit Position Net Cash Position<br>market income plus pension<br>Taxes/transfers as share of gross<br><!-- End of picture text --> _Source_ : World Bank staff calculation using BLSS 2017.

In the presence of multiple taxes and benefits, assessing the progressivity of individual fiscal interventions can be complex. To determine whether a particular intervention is redistributive, we rely on a few different concepts: the Kakwani index, the marginal contribution, and the concentration of each intervention.<sup>25</sup> The effect of specific fiscal interventions is summarized in appendix Table A.6.

> 25 Concentration can be measured using a coefficient that summarizes the concentration curve of a tax or transfer. The curve shows the cumulative percentage of households, ranked from poor to rich by market income, against the cumulative percentage of the tax paid or transfer received by centile. The Kakwani index is defined as the difference between the concentration coefficient of the tax and the Gini for market income. The marginal contribution of a tax

19
- 127 -

# Farm-Level Issues

5.07 Any crop diversification program depends on farmers' adopting new cropping patterns. The technology and incentives necessary for them to do so have been extensively discussed already; the remaining issue is the set of farm-level factors to be addressed by diversification policy. The nature of on-farm constraints, role of the extension service, opportunities for contract farming and mechanisms for organizing farmers, and the responsiveness of farmers to the various types of signals they receive are raised in this section.

# **On-Farm** Constraints

5.08 It is illuminating to contrast the homogeneity of irrigated paddy in an extensive river basin is sufficiently different from the constraints facing upland farmers that decisionmaking models based on farmer behavior in rice systems might provide poor guidance to their behavior when encouraged to grow alternative crops.<sup>40</sup> The uniformity of the environment provided by standing water, coupled with the stability of the market environment provided by a successful price stabilization policy, mean that success in raising rice yields through adoption of new varieties and heavy fertilizer applications does not translate directly into similar behavior if corn, soybeans, peppers, or papayas are introduced into the cropping system. The relatively homogeneity of rice research and extension activities must then give way to the messy diversity of on-farm research on cropping systems. The implied corollary is that far more regional and local research would be needed, not just work within the CGIAR system and national research stations in each country.

- 40/ For an Indonesian example see Heriyanto, and others, 'The On-Farm Research Program for Palawiia based farming systems in Malang District, East Java, Indonesia, 1984-1986." Paper presented at the Farming Systems Research Symposium, Kansas State University, Manhattan, Kansas, October 1986.
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|---|---|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|PG Second MiningSector Inst StrengtheningTA|Mamadou Barry|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Road Sector Project|Sombath Southivong|
|Standard OperatingProcedures of Externally-Financedprojects|Christopher Robert Fabling|
|Standard OperatingProcedures of Externally-Financedprojects|Christopher Robert Fabling|
|Standard OperatingProcedures of Externally-Financedprojects|Christopher Robert Fabling|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
|Irrigation Development and Support Project|Hazem Ibrahim Hanbal|
that equals one if the individual is located in a non-participating municipality.<sup>38</sup> The findings reported in table 7 show that there are no qualitative differences in the direction of the effects to our main findings. However, the magnitude of the point estimates suggests that the fixed effects estimates (table 6) are underestimating the substitution effect in the supply of labor and overestimating the effect on hours of work and income. These results are consistent with the fact that those individuals being more likely to self select into the program and simultaneously being more likely to have a job outside MEP, of working more hours and to have a higher individual income (although the IV estimates for hours worked and income are not statistically significant).

# **5.2 Heterogeneity in the Effects of the Program**

So far we have focused on the average effect of the program. In this section we allow the effect to vary according to some socio-economic characteristics of the beneficiary (gender, education, age and previous experience in the activity) and to some characteristics of the selfemployment activity (e.g., sector, duration). Table 8 reports the fixed effect estimates for the effect of the program and for its interaction with initial characteristics. We use the sample of MEP entrants and all MEP non-participants and look at the probability of having an outside job and on total individual income.<sup>39</sup> We also report the P value for the test that the effect of the program does not depend on the initial conditions. The findings show a significant heterogeneneity in the returns of the project. Females are less likely to substitute away from other sources of employment, and are, therefore, more likely to combine the self-employment

> 38 The number of observations in each regression is smaller than in table 6 because we estimate equation (1) in growth rates and instrument the _changes_ in program participation. In the first stage of the regression (not reported) being located in the “non-participating” municipalities decreases the probability of being a program participant by 0.36 [0.03]*** with an F test of 29.15.

> 39 We do not report the interactions with initial conditions for the other variables previously analyzed because, in most of the cases, we cannot reject the null hypothesis that the effect of the program does not vary with the initial conditions. The only exceptions relate to a smaller increase in total hours worked for the Textiles projects.

22
formal theoretical and empirical testing, the value of trust to social and economic progress is not diminished (Barrett, 1997).<sup>6</sup> As a measure of vertical trust, we use GWP’s _Trust in National Institutions Index_ (NI index). The NI index is composed of four items measuring respondents’ trust in key national institutions (Gallup, 2016). Respondents were asked whether they had “ _confidence in each of the following, or not?_ ” with the options of “(1) How about the military? (2) How about the judicial system and courts? (3) How about the national government? and (4) How about the honesty of elections?” Responses were combined into a single index score for each individual. The index is the mean of valid items multiplied by 100, and is only calculated if respondents had two or more out of four valid scores. As a sensitivity check on the NI index, we study each of the four questions independently. We also examine the effects of food insecurity on more local public institutions (as opposed to national institutions or interpersonal levels of trust), using binary measures of trust in the local police and trust in the financial system and local banks. Further, we also use a principal component approach to reduce potential measurement error (Gillen et al., 2019).

For the horizontal dimension of trust, we use respondents’ trust in friends and family. This binary measure equals one if the respondent answers positively to the question: “ _If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them?_ ” This measure allows us to test whether food insecurity influences interpersonal relationships and social capital rather than only with authority and formal institutions. People who trust friends or family are also more likely to exhibit altruistic behavior and reciprocity, boosting civic cooperation (Putnam, 2000; Uslaner, 2002; Corbacho et al., 2015).

Both GWP trust measures are translated into different languages and standardized, facilitating worldwide comparability. However, the inherent difficulties in assessing a latent trait like trust persist (Barrett, 1997; OECD, 2013). For example, the GWP’s questions measuring trust in national institutions are ultimately subject to ambiguity around respondents’ interpretation of the

> 6 Research identifies trust as one of the most crucial pillars upon which the legitimacy and sustainability of social and economic systems are built (Knack and Keefer, 1997; Alesina and La Ferrara, 2002; Barrett, 2005; OECD, 2013, Algan and Cahuc, 2010).

6
**<u>Figure 5: Comparing change in Herfindahl to absolute level</u>**

<!-- Start of picture text --> Life Non Life<br>Time<br>Period<br>1.8 1.8<br>1.6 1.6<br>1.4<br>1.4<br>1.2<br>1.2<br>1.0<br>One 0.8 1.0<br>0.8<br>year 0.6<br>0.4 0.6<br>0.2 0.4<br>0.0 0.2<br>0 2000 4000 6000 8000 10000<br>Herfindahl in Year (t-1) 0.0<br>0 2000 4000 6000 8000 10000<br>Herfindahl in Year (t-1)<br>1.8 1.8<br>1.6 1.6<br>1.4 1.4<br>1.2 1.2<br>Two 1.0 1.0<br>0.8<br>years 0.8<br>0.6<br>0.6<br>0.4<br>0.4<br>0.2<br>0.2<br>0.0<br>0 2000 4000 6000 8000 10000 0.0<br>Herfindahl in Year (t-2) 0 2000 4000 6000 8000 10000<br>Herfindahl in Year (t-2)<br>Source: Staff Analysis<br>Ht/Ht-1<br>Ht/Ht-1<br>Ht/Ht-2 Ht/Ht-2<br><!-- End of picture text -->

|**Table**<br>|**2: Statistical S**<br>|**ummary of Re**<br>|**sults of Regressi**|**on Lines Comparing**<br>|**Ratios of Herfindahl**|**Indices**<br><sup>_2_</sup>|
|---|---|---|---|---|---|---|
|Case|Dependent|Constant||Slope||_r_|
||Variable||Value|Upper Confidence<br>Interval|Lower Confidence<br>Interval||
|Life|H1/H0|1.111023|(0.000039)|(0.000030)|(0.000049)|3.35%|
||H2/H0|1.120544|(0.000049)|(0.000039)|(0.000059)|7.37%|
|Non|H1/H0|1.040083|(0.000030)|(0.000024)|(0.000035)|5.10%|
|Life|H2/H0|1.067595|(0.000046)|(0.000038)|(0.000054)|10.77%|
||Note: C|onfidence inter|vals shown are ca|lculated on the basis o|f a two sided 95% pro<br>Source: Staff A|bability.<br>nalysis|

# **_Does Market Development Phase Make a Difference?_**

This section investigates whether variation between countries may also be reflective of the stage of development of the market. In the early stages of development, it could be argued that either more or less participants would be expected or that competition is 11
# **5 Annex: Detailed RPSR Indices**

A. Generation and transmission planning index for Kenya and comparators, 2015

||**Kenya**|**Senegal **|**Tanzania **|**Uganda**|**International**<br>**Benchmark**|
|---|---|---|---|---|---|
|**Generation Planning**|86%|43%|43%|43%|56%|
|Countryhas ageneration masterplan|||||94%|
|Countryhas an overall energy plan|||||65%|
|Competent entityis responsible forproducingtheplan|||||88%|
|Inter-governmental committee oversees theplanningunit|||||29%|
|Powergeneration systemplan is mandatory|||||19%|
|Plan leads to timelyinitiation ofprocurement|||||38%|
|Planning process is transparent andparticipatory|||||59%|
|**Transmission Planning**|75%|100%|75%|75%|72%|
|Competent entityis responsible forproducingtheplan|||||100%|
|Explicitlylinked topowergenerationplans|||||88%|
|Plan is mandatory|||||29%|
|Planning process is transparent andparticipatory|||||71%|

- B. Generation and transmission procurement index for Kenya and comparators, 2015

||**Kenya**|**Senegal **|**Tanzania **|**Uganda**|**International**<br>**Benchmark**|
|---|---|---|---|---|---|
|**Procurement of Generation**|100%|50%|100%|95%|85%|
|There is a framework forprocurement|||||82%|
|Country allows International competetive bidding or public<br>auctions forprocurement|||||94%|
|Types ofprocurement methods allowed||||||
|_Unsolicited bids_|||||29%|
|_Direct negotiation_|||||47%|
|_International competitive tendering_|||||88%|
|_Public auctions_|||||41%|
|_Stand-alone capacity market_|||||0%|
|Auction design score|NAP|NAP|NAP|0.86|80%|
|_Country usespublic auctionsforprocurement_|||||41%|
|Clear and comprehensive established rules|_NAP_|_NAP_|_NAP_||100%|
|Crediblepenalties for violatingthe rules|_NAP_|_NAP_|_NAP_||86%|
|Guarantees andpenalties to ensure timelycompletion|_NAP_|_NAP_|_NAP_||86%|
|Standard,non-negotiable contracts|_NAP_|_NAP_|_NAP_||86%|
|Stapled financingterms or risk mitigation instruments|_NAP_|_NAP_|_NAP_||86%|
|No concerns regardingthe transparencyand fairness of the auction|_NAP_|_NAP_|_NAP_||14%|
|Efforts to inform and attract bidders to the auction|_NAP_|_NAP_|_NAP_||100%|
|**Transmission Procurement**|67%|42%|92%|92%|64%|
|Framework forprocurement of new transmission lines|||||59%|
|Methods used toprocure new transmission-|||||69%|
|_Competitive tender_|||||65%|
|_Direct negotiation_|||||24%|
|_Allprojects are awarded to the incumbent transmission company_|||||47%|

Satisfactory result Unsatrifactory result NAP Not applicable NAV Not available 43