rafmacalaba/datause-encoder-data huggingface dataset:
the number of migration episodes completed by each migrant household member (relevant for circular migrants) would be computed with respect to the needs of the household in terms of insurance, purchasing power and savings (Cassarino, 2004). Migrants can also be perceived to either remit or accumulate savings in anticipation of returning home, partially fueled by their social attachments in origin country. Once a target level of overseas earnings/savings is attained, a return decision may be made.

Given the overview of contending migration theories, perception of return migration and its impact on non-farm investments henceforth is conformable with the NELM theoretical underpinnings. Microenterprises face significant credit constraints even in developed settings such as the United States and Great Britain, where mortgage and capital markets are among the world’s most resourceful. This suggests that the formation and survival of small firms, in general, often depends on a relaxation of capital constraints through, for instance, the receipt of an inheritance by the firm’s owner (Blanchflower et al., 1998). Entrepreneurs in developing countries face much less efficient credit markets and more frequent market failures, as the available evidence also indicates that access to credit is among their biggest concerns (Paulson et al., 2004). Therefore, in the absence of efficient credit markets, foreign savings might be seen as particularly important in overcoming liquidity constraints and promoting investment in small businesses, as return migrants, who have generated surplus capital abroad, will have the opportunity to develop new businesses in their nations of origin. Similarly, upon return, migrants may utilize the human capital that they have accumulated throughout their migration episodes to start and successfully manage microenterprises. In this context, human capital may include newly acquired management or technical skills, ideas and entrepreneurial knowledge as well as professional contacts from abroad, and its accumulation is influenced by the type of occupation (skilled vs. unskilled) undertaken abroad.

A number of empirical studies, analyzing the impact of return migration on the development processes of origin countries, have yielded an almost virtual consensus on the positive relationship between return migration and non-farm self-employment in migrant households. Woodruff and Zenteno (2004) in their study of 6,000 microenterprises in Mexico emphasize the importance of remittances for micro-enterprise development in urban areas. A similar finding is shown by McCormick and Wahba (2004) for Egypt: the proceedings from return migration promote investments in small household enterprises, with the largest share of

- 6 -
**Figure 5: Total External Liabilities have built up in India, outpacing GDP; while its composition has tilted towards equity**

<!-- Start of picture text --> FDI Portoflio equity<br>900,000 portfolio Debt Loans 735<br>Deposits Trade Credit<br>800,000<br>Total Liabilities, Index (RHS) GDP, Index (RHS) 635<br>700,000<br>535<br>600,000<br>500,000 435<br>400,000 335<br>300,000<br>235<br>200,000<br>135<br>100,000<br>0 35<br>Million US $<br>Index=100 in 1996-97<br>1996‐97 1997‐98 1998‐99 1999‐00 2000‐01 2001‐02 2002‐03 2003‐04 2004‐05 2005‐06 2006‐07 2007‐08 2008‐09 2009‐10<br>2010‐11 2011‐12 2012‐13 2013‐14<br><!-- End of picture text --> Source: RBI Handbook of Statistics on the Indian Economy; World Development Indicators, World Bank. Capital flows refer to net capital flows.

Indeed this large exposure to foreign capital has also rendered India vulnerable to external shocks, as e.g. was the case during the tapering tantrum of summer 2013, when India was among the most affected countries. Eichengreen and Gupta (2014) analyzed the impact of the Fed’s tapering talk on exchange rates, foreign reserves and equity prices in emerging markets between April-August 2013. They established that an important determinant of the impact across emerging markets was the volume of capital flows that countries received in prior years and the size of their local financial markets. Countries receiving larger inflows of capital and with larger and liquid financial markets experienced more pressure on their exchange rates, reserves, and equity prices once the Fed’s “tapering talk” began. Since India ranked high in terms of the size and liquidity of its financial markets, and in the extent of capital flows it received in prior years, it was an easy target for investors seeking to rebalance away from emerging markets.

# **3.1 Three phases of Capital Flows to India are evident since the early 1990s, which includes a surge-and-stop cycle**

For easy narration, we divide the post liberalization period in India into three phases. A first phase, lasting for about a decade from the early 1990s until early 2000s, is best described as one of modest capital inflows and a managed exchange rate. The exchange rate was devalued twice in the early 1990s and was later floated, but it continued to be defacto managed. The pace of capital inflows doubled during this period, from an average of nearly $5 billion a year in the early 1990s, to $10 billion a year by the early 2000s. The stock of 10
_M_ is the stock of GHGs in the atmosphere, assumed to obey the following law of motion: where _δ_ (≥ 0) denotes a constant rate of decay of GHGs, assuming 0 < _M t_ < max _t_<sup>_E_</sup> _t_ / δ . Discounted damage caused by one unit of emissions at time t1 equals _D(t1)_ , which in the non-stochastic case grows exponentially at rate α starting at _D(t0_ ), and given by The discounted value of damages due to one unit of emissions per time unit emitted forever, starting at _t_ = 0 , is _D_ 0 = Θ 0<sup>/ (</sup> _r_ −α )( _r_ + δ−α ) . Charging for emissions costs at a socially optimal rate along the optimal emissions path requires that the charge _q(t)_ equal _D(t)_ at all times (where _q_ is interpreted as emissions cost alone).

> Suppose _E_ is emitted per time unit from time 0 on. Solving the differential equation for _M t_ yields

_t_ Using that Θ _t_ = Θ 0 _e_<sup>α</sup> , we can calculate accumulated emissions as Here the first term is a “fixed cost” unrelated to the project. Suppose that we retrofit the infrastructure at time _t_ *, eliminating emissions from this project from that point on. We can then again insert for _M t_ (the dynamics of which are now split at _t_ * with _M t_ = _M t_ *<sup>exp(</sup> −δ ( _t_ − _t_ *)) for _t_ > _t_ * ), and write the net social value as −Θ 0 _M_ 0<sup>/ (</sup> _r_ + δ−α ) (which is independent of chosen infrastructure), plus terms amounting to _W(E)_ , that depend on infrastructure type: 9
-5-

# **II.** LONC **RUN** RALATIONSHIPS: TESTS

4. The first question to be analyzed is whether there exists a stable, long-run relationship between the level of commodity prices PCt and the level of interest rates (rt). If so, it may be possible to make quantitative inferences about future commodity prices from observations of changes in interest rates.

5. As a first step we examine the stationarity of commodity prices and the interest rate, employing the integration test, since the co-integration test begins with the premise that for a long-run equilibrium relationship to exist between two variables it is necessary that they have the same intertemporal characteristics. The dynamic property of a time series can be described by how often it needs to be differenced to achieve time-invariant linear properties and provide a stationary process. A series that has at least invariant mean and variance and whose autocorrelation has "short memory" is called I(O), denoting "integrated of order zero". 1/ A series which needs to be differenced A times to become I(O) is said to be integrated of order A , denoted as I(^).

6. The order of integration is inferred by testing for unit roots. The most widely applied unit root tests are: (a) the Durbin-Watson test of Sargan 1/ With "short memory" a small number of lagged observations explains current behavior.
|||||33|
|---|---|---|---|---|
|Paper|265|371|354|358|
|Prting|85|183|108|105|
|Cheadcals|1,210|1,617|1,606|1,404|
|Constuction|570|606|453|430|
|Mechanical Industries|1,403|1A56|2,103|1,916|
|TOTAL|18,266|19,653|19,421|19,309|

Source: Enterprise sample for 1980, 1982, 1984, and 1985.

Tables 4.9 and 4.10 depict the evolution of the **skill** (occupational) structure of the employed Senegalese, nonAfricans, and other Africans, from 1975 to 1985. The Senegalese have been experiencing substantial upward mobility. Their

**TABLE 49**

**SenpaL** Numbe of Upper **L.vd Mana** by **Natonl Groups**

|G3roup||1980|1984|1985|
|---|---|---|---|---|
|Senegalese|91|111|209|230|
|Other Africans<br>Non-Africans|11<br>280|4<br>237|1<br>200|3<br>190|

Source: Svejnar (1984) for 1975. Enterprise sample for 1980, 1984, and 198S.

representation in the workers and apprentices category has decreased, and their. numbers among the skilled workers, technicians, and miedle management categories have increased significantly. As Tabie 4.9 demonstrates, the Senegalese have also become much more numerous among the managers, having replaced non-Africans as the dominant group in 1984. NonAfricans bave virtuatly disappeared from the workers and apprentices group (Table 4.10), and they have also drastically
POVERTY AND INFRASTRUCTURE ACCESS IN SLUMS

# Piped water connections

Table A2a shows the spatial variation of the piped water coverage. As with electricity, we find that all the divisions report at least some households with piped water access suggesting the presence of trunk infrastructure in all divisions. The coverage levels do vary considerably across divisions with a mean of 75 percent and s.d. of 37. The minimum level coverage is 53 percent (Diepkloof/Meadowlands) and the maximum level is the full 100 percent coverage (Sandton/Rosebank). We also find that 55 percent (6 out of 11) of the divisions have at least one or more EAs that completely lack access to piped water and about 9 percent (23 out of 253) of all EAs have no access.

**Table A2a. Johannesburg piped drinking water: coverage insights**

|||# of EAs||Covera|ge (percen|tage of ho<br>A|useholds wit<br>i|h access)<br>EA||
|---|---|---|---|---|---|---|---|---|---|
||Number|with no|Number|Across||cros|consttuen|s||
|Division|of EAs|piped water|of HHs|divisions|min|max|med|mean|sd|
|Alexandra|35|0|738|93|45|100|100|93|16|
|Central region|17|0|332|94|5|100|100|94|23|
|Diepkloof / Meadowlands|27|5|545|53|0|100|48|53|44|
|Diepsloot|16|4|321|63|0|100|100|63|47|
|Doornkop / Soweto|45|4|941|67|0|100|85|67|38|
|Ennerdale / Orange Farm|58|6|1,158|67|0|100|95|67|40|
|Johannesburg South|4|1|81|69|0|100|88|69|47|
|Midrand / Ivory Park|31|0|568|94|21|100|100|94|17|
|Northcliff|3|0|59|68|5|100|100|68|55|
|Roodepoort|11|3|216|64|0|100|100|64|50|
|Sandton / Rosebank|6|0|139|100|100|100|100|100|0|
|All|253|23|5098|75|0|100|100|75|37|

Table A2b presents the results from the household level logistic regression results for piped water access. As in the case of electricity, we again find that (at 10 percent significance level or less) tenancy status does not play much of a role in terms of a household’s access to piped water, but whether the household lives in a shack or not does. Specifically, the likelihood of a shack household having access to piped water is only about 16 percent of that of a non-shack household. We also find that, after controlling for demand side factors, residential location also matters greatly in determining access. For example, the likelihood of households residing in Roodepoort of having access to electricity is only 7 percent of those residing in Alexandra division.

50
**<u>Table 8. Household Level Fixed Effect Estimates for Hypothetical Sales Prices at Plot Level</u>**

||D<br>|ependent variable: Lo<br>|gof saleprice(Rs/Acr<br>|e)<br>|
|---|---|---|---|---|
|Tenancy land dummy|-0.429***<br>(16.94)|-0.430***<br>(16.97)|-0.428***<br>(16.45)|-0.433***<br>(15.05)|
|75/25 sharing rule||||0.020<br>(0.39)|
|Area (log)|0.031|0.035|0.035|0.036|
||(0.59)|(0.63)|(0.63)|(0.64)|
|Log area squared|0.001|0.002|0.002|0.002|
||(0.29)|(0.32)|(0.33)|(0.33)|
|Dist. to homestead in|-0.032***|-0.031***|-0.029***|-0.029***|
|km (log)|(3.87)|(3.66)|(3.61)|(3.60)|
|Irrigated land|||0.017|0.017|
||||(0.81)|(0.79)|
|Soil quality measures|No|Yes|Yes|Yes|
|Number of|1,774|1,774|1,774|1,774|
|households|||||
|No. of obs. (plots)|8,727|8,677|8,677|8,677|
|R-squared|0.29|0.29|0.29|0.29|

Robust t statistics in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%. Standard errors adjusted for clustering at village level.

23
Figure 3: Discount on Israel DCI Bonds Compared to US Treasury <!-- Start of picture text --> 14 annual average rate %<br>12 10-year US<br>Treasury<br>10<br>8<br>6<br>Fixed rate<br>4<br>2<br>0<br>1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003<br><!-- End of picture text --> _Source: Bank of Israel and U.S. Federal Reserve_ Comparison of interest rates on fixed-rate DCI bonds versus those on 10-year UST notes shows the large extent of discount offered by the Jewish diaspora in purchasing these bonds. Interest rates on DCI fixed-rate bonds averaged about 4 percent from 1951 to 1989. While the 10-year UST rates were lower than 4 percent only from 1951 to 1958, they have been higher than 4 percent since. Of course, as the UST rates kept on rising rapidly in the 1980s and buying DCI bonds at 4 percent implied steep discounts, demand for the fixed-rate issues waned in favor of floating rate debt (Figures 2 and 3). The sharp decline in US rates since 2002 has, however, re-kindled investor interest in fixed-rate DCI bonds. Note that the degree of patriotic discount has dwindled in recent years and rates on fixed-rate DCI bonds have exceeded 10-year UST yields. This is perhaps owed to the fact that younger Jewish investors are seeking market-based returns. But perhaps more importantly, the decline in patriotic discount is also due to the Ministry of Finance developing alternative sources of external financing such as negotiable bonds guaranteed by the U.S. government, non-guaranteed negotiable bonds and loans from banks. These instruments, which trade in the secondary market, provide alternative avenues for acquiring exposure to Israel. Consequently, interest rates on DCI bonds have to be competitive; in fact a tad higher than those on the above alternative instruments given that DCI bonds are non-negotiable (Rehavi and Asher 2004).

7
used Montemayor’s (2008) results to gauge how well the SSM triggers would separate appropriate action from inappropriate, the criterion he himself applies is how often developing countries would be allowed to impose additional duties, e.g., ‘slightly higher volume and price thresholds ... would not seriously compromise access rates.’ (p. 11) By this standard, the ideal parameters are those without limit on magnitude of remedy or on when remedy can be applied. The criterion of accuracy – how often the SSM as a decision rule would indicate the correct versus the incorrect decision – slips out of consideration.

The exchange of SSM proposals in Geneva has been captured by the same mentality: exporters submitting proposals that would allow fewer SSM restrictions, importers submitting proposals than would allow more. Functionally speaking, this is part of the market access negotiations – agreeing the limits beyond which each government reserves the right to unilateral action – rather than an attempt to design a policy decision mechanism.

If the SSM discussion is about creating an effective safeguard mechanism then it should be about creating a good management tool. That management tool should help a government to reach a correct decision and to sustain that decision among its various constituencies. This suggests that the discussion should be about process rather than about criteria/formulas, particularly about finding a role for interested parties so that they have a sense of ownership/acceptance of whatever decision is reached.

A second comment relates to the number of objects at play relative to the limited policy instrument the SSM mechanism will provide.

The SSM negotiations reflect a multiplicity of concerns/objectives; among them:

- Allowing policy response to departures from trends but not to trends

- The length of departures from trends

- Allowing policy response to random short-term variations but not to regular or seasonal short-term variations

- Food security

- The pace of shifting resources from agriculture to other sectors

- The wisdom of imposing year-to-year adjustments on resources that have comparative advantage in agriculture.

Viewed from an unflattering perspective, the SSM negotiations are an attempt to reduce the set of management tools needed address these concerns to an arithmetic formula for tariff rates. This view brings forward the SSM negotiations as an example of a problem that Aaditya Mattoo and Arvind Subramanian (2009) have presented in a broader context: the Doha Round has taken on an agenda trivial to the problems the international community now faces. The tool set to which the negotiators have limited themselves may be inadequate to manage the issues, complications and interactions at hand – an attempt to control the side effects of remedies not outlined for problems not taken up.

39
smaller than for the BDM sample and are not statistically significant. This is in line with the fact that this sample of entrepreneurs is richer, and probably less affected by liquidity constraints.

# **4.2 Correlates of Willingness to Pay**

There are several market failures than can justify subsidizing business training. The first, and one for which there is some suggestive support in the literature (e.g., Karlan and Valdivia (2011); Bloom and Van Reenen (2010)) is that of an information failure, whereby the value of business training services is not understood by entrepreneurs, and may be particularly understated by those with the most to gain, who do not realize how poorly run their firms are. A second market failure is credit constraints: firms may find it harder to borrow to finance training, an intangible asset, than to finance assets, which can be seized by a bank in the event of non-repayment. There is strong evidence that many small firms are credit-constrained, but much weaker evidence to support the view that this is the key constraint to them purchasing business training services. A third possibility is insurance market failures, with firm owners reluctant to take training even if they think it has a high expected payoff, because they are unable to insure against the possibility that it does not work. There is some recent evidence to support the view that risk is a constraint to start-up and investment in small businesses (e.g. Bianchi and Bobba (2012)), but no evidence we are aware that shows that alleviating this constraint leads to more purchases of training. Finally, an alternative is that there is no such market failure, and the reason firms do not buy business training without subsidies is that they have low returns to undertaking such training.

We draw on these hypotheses to examine the extent to which existing business practices, self-perception about existing skills, access to finance, risk preferences, and expected returns determine willingness to pay for training. This enables us to see the extent to which charging for business training will affect not just how many business owners receive training, but also which entrepreneurs will get trained.

We first use our experimental treatments to determine whether WTP varies with liquidity effects and framing. Table 5 presents the results from regressing elicited WTP in the BDM sample on observable characteristics measured at the baseline survey. We include fixed effects to control for week and location of the demonstration. Column (1) includes only the randomized treatment variations; we confirm that neither the possibility to pay in installments, nor the discount frame or their combination has significant effects on WTP. Columns (2) through (6) then examine different potential determinants of demand. Col18
Where p represents the quantity of imports for product p, from exporter i at time t, is the HS 10 digit elasticity of substitution for product p of the importing country (taken from Broda and pp pp ln xx σσ Weinstein, 2006), ln q q q p is the quality and p the unit price of the imported product. p is the price index of the product and pp p is the expenditure on product p. pp qq ln pp Note we estimate equation 2 using: PP ww Where F p varieties of product p (<sup>denotes an HS 10 digit product-time fixed effect, which absorbs the price index for</sup> p ) as well as demand expenditure on these products ( p ) (see discussion in Breinlich et al, 2016). (Log) quality is then estimated as the residual p from ln PP ww regression 2, scaled by the elasticity of substitution: pp εε̂ The intuition for the quality measures is it reflects market shares, conditional on prices in the destination country, the United States. The resulting measure is often interpreted as a relative ranking of quality _within_ each product-destination market combination. We follow this interpretation. Firstly, we estimate regressions based on this within variation at the exporterproduct level (as we note in section 4). Secondly, where we examine heterogeneity by initial product quality relative to the “quality frontier”, i.e. the highest quality exports, we define the frontier at the HS 10 digit level, consistent with the quality measure.

Our sample illustrated in Table 1 spans 59 countries, both developed and developing, over a 15year period (2000-2015) for 16 manufacturing industries (2-digit ISIC rev.4) and 5,646 unique HS 10-digit products.

13
_Trends in Private Sector Development in World Bank Education Projects_

# Contents

|_Forewo_|_rd_<br>_...................._<br>|ii<br>|
|---|---|---|
|_Abstrac_|_t_<br>_...................._<br>|iii|
|_Executi_|_ve Summary ....................._<br>|iv|
|I.|Introduction and Background .1||
|II.|Market for Education.|3|
|III.|Government's Role in the Marketplace .10||
|IV.|World Bank Lending for Private Sector Development<sup>in Education .12</sup>||
|V.|Findings .15||
|VI.|The Future Role of the World Bank Group in<sup>Education .18</sup>||
|VII.|Conclusion .21||
|_Annex._|Country Case Studies<br>..................|23|
|_Bibliog_|_raphy_<br>_..................._|_44_|

i
and trustees, and overturn the decisions of regulatory bodies. Guidelines for determining violations of labor and employment laws were also absent-and the arbitrariness of import duty exemptions has already been referred to.

But the most critical constraints on private sector competition and economic efficiency were the laws governing entry, exit, and operational flexibility. A!though competition policy had been set in legislation, the existence of market power, extensive vertical integration, and a highly concentrated wholesaling system suggest that enforcement was weak. Important market segments in the Kenyan economy were controlled by single monopolies, generally parastatals, or by just a few producers. Nearly 60 percent of sales in the economy was estimated to occur in oligopolistic markets; in manufacturing, it was about 40 to 50 percent. Moreover, most manufacturers were prohibited from marketing directly to retailers or the public, thus protecting the marketing power of parastatals-and nowhere was this more pervasive than in the agricultural sector. Exit laws were essentially "winding up" policy-focusing on the disposition of assets without any provision for interim legal protection to reorganize. In practice, adjudication took four to ten years, placing enterprises in limbo as their operation came to a standstill and their assets were tied up.

Finally, empirical work indicates that licensing requirements imposed significant monetary and transacions costs on firms (table 4). A survey of enterprises showed that the cost of annual licenses-including direct license fees, agent fees and bribes, and transaction costs for enterprise staff time-was very high both as an absolute amount and as a proportion of sales; moreover, the relative cost of licenses 35