rafmacalaba/data-use-mentions-extended huggingface dataset:
# **5. Improving the Rural Investment Climate for Businesses**

Improving the RIC for businesses appears to be a necessary condition for incentivizing activities that raise rural incomes. The proliferation of such activities lays the foundation for improved livelihoods, and promises to provide an expanded resource base from which community health care, education, transportation, and infrastructure can draw.

By combining major constraints perceived by rural entrepreneurs, assessed by RIC indicators, and econometric modeling results, the following areas are identified as critical RIC components for improvement: market demand, access to markets, access to finance, business/agriculture services, management, and technology. Labor and telecommunication could be also added to the list. Improving these areas would lessen the obstacles to starting a business and the reasons for closing it and it would further increase income generation activities. For women entrepreneurs, a security issue has to be resolved. These income-generation activities could also boost the population of the rural communities through increased economic activities.

# **5.1 Increase Market Demand**

It is vital to increase market demand in rural areas if rural businesses are to grow. If market demand stays the same while income generation activities increase or existing businesses expand, profitability may decrease due to the limited number of customers. If there are too many competitors relative to the existing demand, then prices may come down due to excess supplies and enterprises may not be profitable. If there are too few competitors, market demand may exceed the supply, giving entrepreneurs a chance to expand their businesses to meet the excess demand. Major obstacles perceived by rural entrepreneurs for weak demand or too many competitors are 43 percent by farm entrepreneurs and 37 percent by nonfarm entrepreneurs according to the Yemen RIC survey.

There are a number of ways to enable entrepreneurs to better access demand and reduce the frictions that impair their ability to supply products targeted on market opportunities. These include:(i) developing or improving marketplaces with required amenities; (ii) improving access roads and transportation for customers to come
and more than four fifths in terms of weight (see Table 2).<sup>8</sup> Certain shipments are sealed in Matadi to pass customs formalities in Kinshasa. Matadi therefore accounts for a considerably larger share of physical entry into the DRC than reported in Table 2. Kinshasa airport is also a significant entry point, accounting for some 10 percent of import values.

> 7 Recent research in economic geography indeed suggests that urbanization is a key engine of growth in developing countries, and that limits to the formation of urban agglomerations can constitute a severe obstacle to economic development (Deichmann _et al_ ., 2008; Brülhart and Sbergami, 2009).

> 8 We use data for 2007, as these statistics are more complete than those we received for 2008 and 2009. Table 2 most likely underreports the share of the ports of Boma and Banana/Kinlau. According to tonnage data for 2008 obtained from the logistics company SDV-Agetraf, the volume of imports entering through Boma and Banana/Kinlau amounted to 9 percent and 13 percent respectively of the volume of imports entering through Matadi.

10
-- End of picture text --> _Source:_ World Bank staff calculations based on NHBPS 2014/15.

Many women do not even enter the labor force: women generally, and female youth in particular, represent the highest share of the population out of the labor force. For men it is more common to be out of the labor force before the age of 24, while women are likely to be out of the labor force across all age cohorts. Three in every four young women (75 percent) are not in the labor market, compared to just over half (54 percent) of young men. The percentage out of the labor force varies significantly across working-age men and women: only 3 to 13 percent for men aged 25 to 64 compared to 58 to 66 percent for women (Figure 5).

> 6 The pattern is the same for other categories (men and adults); compared to urban areas, living in rural areas increases the chances for men and adults to be employed by 35 percent and 41 percent, respectively. Data based on logistic regression model using the NHBPS 2014/15.

11
<br>(82)|
|Are commercial banks required bysupervisors to have external credit ratings?|14|5|18|
|Are all banks operating in your country (including foreign bank branches) required<br>to make available to the public their annual financial statements:<br>On an individual basis?|92|84|95|
|On a consolidated basis(if applicable)?|89|92|88|
|Do supervisors require banks to publicly disclose:<br>All fines and settlements resulting from non-compliance with regulations?|22|16|24|
|Other information not required byfinancial reportingstandards?|41|49|38|
|Are bank directors legally liable if information disclosed is erroneous or<br>misleading?|95<br>(89)|97<br>(92)|95<br>(88)|
|**B.**<br>**Disclosure Practices of Banks**|**% Yes**|**% Yes**|**% Yes**|
|Do banks disclose to the public:||||
|Full audited financial statements?|94|92|95|
|Off-balance sheet items?|78|86|74|
|Governance and risk management framework?|73|86|68|
|Regulatory capital and capital adequacy ratio?|77|86|74|
|Transactions with related parties?<br>|70|86|64|
|Any other material information?<sup>*</sup><br>|74|81|72|
|Scope of consolidation?<sup>**</sup>|76|89|71|

Source: Calculations based on the 2011–12 Bank Regulation and Supervision Survey, which reflects values as of 2010. Values in parentheses refer to the 2007 Bank Regulation and Supervision Survey, which captures data as of 2005. ADV:
Adult >=25 years old<br>‘ote Standard enorschsteredon survey wave<br><!-- End of picture text --> <!-- Start of picture text --> 2<br>go7<br>E<br>=.gBo2<br>a32<br>*<br>E<br>B a<br>%<br>a g °<br>Apr-2020 May-2020 Jun-2020 Jul2020 Aug-2020 Sep-2020 Oct-2020 _Nov-2020 Jan-2021 Feb-2021 Mar-2021<br>Months from March 2020<br>—®— Young <25 yearsold = ——®— Adult >=25 years old<br>pomp<br><!-- End of picture text --> <!-- Start of picture text --> 2i:<br>a=E|<br>&<br>:fe<br>aB=3°ro)<br>3<br>aZ<br>5 +<br>e<br>i<br>ona°<br>2 a<br>4 Apr-2020 May-2020 Jum-2020 Jul-2020 Aug-2020 Sep-2020 Oct-2020 Nov-2020 Jan-2021 Feb-2021 Mar-2021<br>Months from March 2020<br>—®— Young <25 yearsold —®— Adult >=25 years old<br>‘Note: Standard errors clustered on survey wave<br><!-- End of picture text -->
New growth<br>2012 2006<br>Source: Author’s classification of SPOT5<br><!-- End of picture text --> Although the goal of classifying SPOT5 imagery was to explore how well coarser imagery could be used to analyze urban growth over time, several interesting trends emerged through a cross city comparison. Figure 19 below summarizes the land cover within 5kms of each city’s CBD. The cities have been ordered according to population size, with Kinshasa and Lagos being two of the most populated cities located near the Y‐axis, and Freetown with less than 1 million inhabitants located at the very end.<sup>53</sup> Returning again to Maputo with a population of roughly 1.2 million, the chart shows that within 5 kilometers of its

> 53 Population data taken from <u>http://www.citypopulation.de/, a website that compiles national census data.</u>

29
, Z. Z. Guan, T.S. Jayne and R. Black. 2009. “Factors Influencing the Profitability of Fertilizer Use on Maize in Zambia.” _Agricultural Economics_ 40: 437-446.

Mundlak, Y., 1978. “On the pooling of time series and cross section data.” _Econometrica_ , 46, 69– 85.

World Bank. 2007. “ _Malawi: Country assistance strategy FY2007-FY2010.”_ Washington, DC: The World Bank.

World Bank. 2015. _The cost of the gender gap in agricultural productivity in Malawi, Tanzania, and Uganda_ . Washington, D.C.: World Bank Group 31
are constructed. If credit growth in asset class _i_ of bank _j_ is less than the average credit growth, then the probability of default in asset class _i_ of bank _j_ is equal to the aggregate PD, that is, _PDi_<sup>S</sup> , _j_<sup>=</sup><sup>_PD_</sup> _i_<sup>S.28If, however, credit growth for bank</sup><sup>_j_is greater than the average</sup> credit growth, then the probability of default under scenario S is scaled up by an amount that depends upon how much larger credit growth was for this bank in a given asset class, relative to the median credit growth in the entire system.

Due to the restriction of a zero weight when _CGi_ , _j <_ median( _CGi_ ), the scaling term [ _CGi_ , _j −_ median( _CGi_ )]/[max ( _CGi_ ) _−_ median( _CGi_ ] is bounded between 0 and 1. This implies that the maximum amount by which the PD for bank _j_ in asset class _i_ can increase over the aggregate TTC PD due to the penalty is given by the size of the scaling parameter _κ_ . The effective bounds on _PDi_<sup>S</sup> , _j_<sup>are thus given by [</sup><sup>_PD_</sup> _i_<sup>S,</sup><sup>_PD_</sup> _i_<sup>S+</sup><sup>_κ_].Should it be the case</sup> that no annual credit growth data at the individual bank level are available, then the _κ_ parameter can be set to 0. The consequence of this is that each _PDi_<sup>S</sup> , _j_<sup>then collapses to</sup><sup>_PD_</sup> _i_<sup>S.</
this regard, target setting, and monitoring are key elements for innovation. Data suggest that Chinese firms are, on average, stronger in monitoring, followed by the development of human resources policies (incentives); the capacity to set long-term targets emerges only as the third performing area (Figure 16). Vietnamese firms are also stronger in monitoring, and in this case with a superior performance in comparison to China; the capacity to set long-term targets is the second highest performing area. When taken together, these results suggest that the performances of both China and Vietnam are below the median countries in all domains (except for incentives, in the case of China), which points to a potential scope for improvement.<sup>14</sup>

**Figure 16. Average score across managerial dimensions: 1(“worst practice”) to 5(“best practice”)**

<!-- Start of picture text --> 5.00<br>4.50<br>4.00<br>3.50<br>3.00<br>2.50<br>2.00<br>1.50<br>1.00<br>0.50<br>0.00<br>operations monitoring targets incentives<br>China Vietnam top performer(country) median (country)<br>Source: Own elaboration based on WMS dataset.<br>Note: The country score is calculated as a simple average across firms, for each country<br><!-- End of picture text --> Moving the focus of the analysis from the average to the entire distribution of management quality score, Figure 17 plots the kernel density functions of China and Vietnam against the United States, the top performing country in the survey. The Kolmogorov-Smirnoff test (for which the null hypothesis is the equivalence of compared distributions) is also reported; in both cases, there is evidence to reject
losses (% of total output) are obtained from the _World Development Report 1995,_ the World Bank.

2. Telephone Mainlines (per 1,000 persons) in 1992. This variable is obtained from the _World Development Report 1995,_ the World Bank.

3. Roads in good condition (km per million persons) in 1988. This is calculated as Road density (km per million persons) x Roads in good condition (% of paved roads). Data are from the _World Development Report 1994,_ the World Bank.

4. Population with access to safe water (% of total) in 1990. Data are from the _World Development Report 1994,_ the World Bank.

5. Public infrastructure index. It is the simple average of the standardized values of the above fou; indicators. All indicators are standardized by computing z-values, that is, dividing the deviations from the mean by the standard deviation.

Growth Rate: The growth rates of real per capita GDP from 1980 to 1992 are calculated using the leastsquare method. Real per capita GDP data are from the World Bank National Accounts.

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**Table 5: Transition Matrix Based on the Synthetic Panel 2010/2018**

|**Status in 2010, 2018**|**Lower-bound estimate (%)**|**Upper-bound estimate (%)**|
|---|---|---|
|_NEET, NEET_|46.66|35.95|
|_NEET, non-NEET_|4.35|17.82|
|_Non-NEET, NEET_|0.00|10.71|
|_Non-NEET, non-NEET_|48.98|35.51|

_Notes:_ results are restricted to the sample of individuals aged between 15 and 24 in 2010 and between 23 and 32 in 2018. “Lower” and “Upper” refer to the two bounds on mobility; for immobility, “Lower” is the upper bound and “Upper” is the lower bound. Upper-bound estimates are based on 50 replications. Individual-level sampling weights are applied.

The estimated NEET rates for 2018 can be directly derived from the transition matrix by adding up the share of people in two groups: (NEET, NEET) and (non-NEET, NEET). For instance, the lowerbound estimate of the NEET rate in 2018 amounted to 46.66 percent, which is the estimate displayed in the respective cell in Table 4. Similarly, the upper-bound estimate consists of the chronically NEET (35.95 percent) and the (non-NEET, NEET) group (10.71 percent), resulting in the estimate displayed in the respective cell in Table 4 (46.66 percent).

The results suggest that the NEET condition tends to persist, as is hinted at in the paper’s title. Comparing the share of NEET in both periods to those who were NEET in 2010, we found that those NEET in 2010 had a 70 to 90 percent probability of remaining NEET after 10 years, and only a 10 to 30 percent probability of escaping from the condition. This impression of substantial immobility
is often done indirectly, through least squares regressions testing whether idiosyncratic income shocks have a significant effect on individual consumption after controlling for the average consumption of all agents. Obstfeld (1994), Canova and Ravn (1996), and Lewis (1996) are some leading examples of this literature applied to cross-country aggregate data.<sup>3</sup> These conventional tests can be informative about whether perfect risk sharing holds But if the null is – as is almost the case – in empirically. hypothesis rejected invariably

> 1Market completeness represents a sufficient, but not necessary, condition for perfect risk sharing. The same outcome might be achieved by, say, agreement between governments to a suitable system of transfers across countries.

2The reason is that financial integration may also open the door to the propagation of financial turbulence from abroad. For example, Devereux and Yu (2016) find that financial integration reduces the severity of crises as a result of better diversification, but makes them more frequent due to increased opportunities for contagion. As a consequence, the overall degree of risk faced by consumers may rise or fall relative to a situation of financial autarky.

> 3Cochrane (1991) and Townsend (1994) present early implementations of risk-sharing tests based on household level data.

1
**Figure 3. 15  Reasons for not requesting a loan from the informal sector**

<!-- Start of picture text --> Other 1.5%1.5%<br>High cost of credit 2.0%5.4%<br>Lack of collatera/guarantees 2.6%2.7%<br>No w ork/job 4.3% 12.3%<br>Not enough income 7.2% 16.0%<br>Prefers ow n resources 15.2%16.4%<br>Don't like to get into debt 22.2%22.4%<br>Didn't need 26.6% 41.5%<br>0% 10% 20% 30% 40% 50%<br>Banked Unbanked<br><!-- End of picture text --> _Source: DANE household study of Bogotá, 2003_

# **3.5 THE COSTS OF BEING UNBANKED**

29. The survey does not itemize costs of informal and formal financial services. Further analysis is encouraged in this regard. Conceptually, the costs paid for financial exclusion by the unbanked include:

- The cost of informal savings in terms of insecurity, values lost to inflation and to interest charges from lay away plans, or of outright losses in lottery programs.

-

- The costs of cashing checks at CCO’s

-

- The costs of remittances

- The costs of lost IVA returns (i.e. 2% of all purchases which are returned through bank accounts)

- The costs of paying bills – time lost traveling to utility companies to make payments in person

- The costs of informal loans, averaging 10% per month or 150% annually, versus 15- 27% annual interest rates for bank loans and 36% for credit cards.

# **3.6 REASONS FOR BEING UNBANKED**

30. In answer to the
over the life cycle in some countries. In order to achieve a welfare-maximizing smooth consumption curve, households should accumulate savings during their work life span and draw on their wealth upon retirement, according to the Life-Cycle Hypothesis (Feldstein, 1976; Munnell, 1974; Jappelli & Modigliani, 2006). Pension systems allow retirees to annuitize a portion of their savings. But while homeowners dedicate a considerable portion of lifetime savings to their house, the elderly have few means of tapping their accumulated housing wealth (Shan, 2011). Citizens with defined contribution pension schemes in particular may even be dissuaded from becoming homeowners in the first place

> 2 Homeownership numbers taken from Wikipedia rankings, complied from Eurostat and national housing data <u>https://en.wikipedia.org/wiki/List_of_countries_by_home_ownership_rate.</u> Pension replacement rates estimated in ‘Pensions at a Glance’ publication 2019 <u>https://www.oecd-ilibrary.org/sites/b6d3dcfc-en/1/2/5/2/index.html?itemId=/content/publication/b6d3dcfcen&_csp_=a8e95975da55b0299df9e90b37215621&itemIGO=oecd&itemContentType=book.</u>

7
sure of innovation inputs. For example, OECD (2018) uses the number of scientists and engineers as an indicator for measuring a country’s technological human resources. Maloney and Caicedo (2017) present a historical analysis of the impact of engineers density on technological intensification and structural change. de Rassenfosse and van Pottelsberghe (2009) use the number of full-time scientists and engineers as a measure of innovation effort in a patent knowledge function and show evidence of a positive relationship between research effort and patents fillings. Huang and Yu (2011) also use the number of R&D personnel as a measure of in-house R&D, and analyze the effect of competitive and non-competitive R&D collaboration. Finally, Cirillo et al. (2017) use the number of technical-scientific workers as a proxy of innovation when looking at the impact of innovation on within-firm wage inequality in Europe.

We follow this literature and use the measure proposed for Brazil by Ara ́ujo et al. (2009) and Taveira et al. (2019) based on the firm’s share of technical-scientific employees (PoTec) as a proxy for R&D investments (see Table 2 for definition). Ara ́ujo et al. (2009), using RAIS and PINTEC databases, show that PoTec has a high correlation - between 0.8 to 0.9 - to intramural and extramural R&D expenditure. We also compare the R&D expenditures by states, according to the latest PINTEC survey in 2017, with our PoTec firms by state in 2017 and find a correlation of 0.81. Thus, in the absence of direct data on innovation expenditure for the firms in the census, the PoTec approach appears as a good proxy of R&D expenditure intensity. More importantly, it allows using the employer-employee census to follow firms and workers over time and to match worker’s characteristics with those of the innovative and non-innovative firms. Exploiting these dynamics allows exploring transitions from noninnovative to innovative status, which is critical
rise in trucking costs. The lower probability of securing the next trip from the destination may have led to an increase in cost in the current route. Drivers needed to be compensated for higher health risks.

To establish the average increase in freight rate during the lockdown and post-lockdown periods, we revert back to trip level data from JDL trucks. We define two dummies to capture the national lockdown ("lockdown") and post-lockdown ("post") periods. We run a before-after (single difference) regression of the log of freight rate on the post dummy which takes the value of unity if the date is after June 30, 2020, and zero otherwise.<sup>11</sup> This regression includes the log of the distance between OD pair and origin and destination fixed effects. Column 1 of Table 3 reports the estimates from this simple regression excluding the lockdown period from the sample. The coefficient of post dummy indicates a nearly 32 percent increase in freight rate during this period. To capture the heterogeneity with respect to distance, the regression in column 2 introduces the interaction of post with the log of distance. The interaction term has a positive sign indicating a larger increase in freight rate for longer distance trips. The regressions so far excluded the lockdown period. In column 3, we include the lockdown period (March 24- June 30, 2020) in the sample and the lockdown dummy in the regression. Consistent with Figure 3, the estimate indicates about a 39 percent increase in freight rate during the lockdown period (column 3). When interaction with distance is introduced (column 4), the estimate implies a doubling of the average freight rate for shorter trips and a lower increase for longer distance trips during the lockdown period. The results for postlockdown in column 4 are similar to that in column 2.

The regression results suggest a heterogeneous increase in freight rates between lockdown and postlockdown periods, and with respect to the distance between OD pairs. With such heterogeneity, the policymakers may want
countries.<sup>4</sup> The studies most relevant to our research are those by Ibanez et al. (2022) and Urbina Florez et al. (2023), which document PEP’s positive impacts on Venezuelan migrants’ consumption and labor income.<sup>5</sup> Secondly, we add to a vast literature examining how policy shapes fertility (e.g., Lalive and Zweim ̈uller, 2009; Milligan, 2005; Bailey, 2012). We focus on how immigration policy influences immigrant fertility. Low fertility rates and longer life spans in developed and developing countries have sparked government interest in understanding the potential role of immigration policy to bolster public pension systems. Immigration could alleviate the caused an number of retirees and could fiscal pressure by increasing support these programs through the growth of a workforce with higher fertility rates than those of natives (e.g., Storesletten, 2000). While this impact might be limited in nations with relatively low immigration and very low fertility rates (e.g., South Korea), it could be relevant for others such as Colombia.

Finally, our study contributes to a broader literature on immigrant integration(e.g.,Abramitzky et al., 2012, 2014; P ́erez, 2021). Given declining global fertility trends and increased forced it is vital to how can into host so- migration, study policy shape immigrant integration cieties. The higher fertility rates of immigrants compared to natives are controversial. This is particularly true given large migrant inflows over a short time span, as they can constrain the host country’s health care system and elicit opposition from natives.

# **II INSTITUTIONAL CONTEXT: THE PEP REGULARIZATION PROGRAM**

Colombia is the main recipient of Venezuelan migrants. According to data from the United Nations Refugee Agency, approximately 2.5 million Venezuelan migrants had arrived in Colombia by February 2022, with the vast majority arriving since 2016. This number does not include undocumented migrants