rafmacalaba/datause-encoder-data huggingface dataset:
KENYA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE is $1.7 billion (table 13). Most of the rest of the gap is found in the power sector, where an additional $439 million is needed to meet the country’s development goals.

**Table 13. Funding gaps by sector**

<u>US$ millions</u>

||ICT|Irrigation|Power|Transport|WSS|Total|
|---|---|---|---|---|---|---|
|Spending needs|529|16|1,019|474|1,930|3,968|
|Existing spending|529|3|471|474|167|1,644|
|Efficiency gains|0|—|109|44|77|230|
|Funding gap|0|—|439|44|1,686|2,094|

Source: Derived from Foster and Briceño-Garmendia 2009.

Note: Potential overspending is not included in the calculation of the funding gap, because it cannot be assumed that it would be applied toward other infrastructure sectors. — = data not available.

# What else can be done?

The funding gap can be addressed only by raising additional finance or, alternatively, by adopting lower-cost technologies or less-ambitious targets for infrastructure development. The size of the gap forces Kenya to be realistic about targets and to be very deliberate about how it spends the relatively limited resources available.

Adopting lower-cost technologies could substantially reduce the cost of meeting the posited infrastructure targets, and halve the size of the funding gap. For example, meeting the Millennium Development Goals for water supply and sanitation with lower cost technologies than previously used (such as stand posts, boreholes and improved latrines) could reduce the associated price tag from $1.9 billion to $1.0 billion each year. Similarly, meeting transport connectivity standards using lower cost road surfacing technologies (such as single surface treatment) could reduce the associated price tag from $0.47 billion to $0.25 billion. The overall savings from these measures would amount to $1.1 billion or more than half the country’s infrastructure funding gap; underscoring the importance of technology choices.

If Kenya had no means of raising additional finance for infrastructure, the only way to meet the targets here identified would be to take a longer period of time than the decade contemplated at the outset of this exercise. If the country were to make efficiency gains while holding spending at current levels, it could meet the identified infrastructure targets in 18 years—that is, it would reach the targets by 2026. Without tackling inefficiencies, the those targets would not be reached for several decades.

Within the overall funding envelope, it will be very important to carefully prioritize infrastructure investments. Given the magnitude of the country’s funding gap, it will not be feasible to resolve all pending infrastructure issues at once. Hence the need to identify priorities. The foregoing analysis of achievements and challenges suggests the importance of prioritizing key infrastructure interventions for the economy, such as improving the port of Mombasa and expanding generation capacity.

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The cost of living variable enters very significantly and of important magnitude in the sector of origin. The strong positive coefficient on the destination is unexpected. It may perhaps be consistent with the view of cost of living being a measure of expectations for future income growth as discussed earlier. Alternatively, as with many of the explanatory covariates, the cost of living is likely to be endogenous to immigration flowsgrowing population pushing up the cost of housing, goods and services- and hence potentially biased. However, the lack of credible instruments precludes a serious attempt to deal with simultaneity bias so we simply leave this as a caveat.

There appears to be some interaction between the amenities and networking variables. In the absence of the latter, the amenities variable enters with predicted signs, but again in the relative/free standing format that suggests that amenities may be correlated with an omitted credit constraint variable. Including networking reduces the significance of the relative amenities term in virtually all specifications. The reason is not clear although it may be that the cumulative migration from origin to destination of the past that is the networking term is especially related to the relative amenities levels.

# _Labor Market Variables_

Preliminary estimations of 1a and 1b found both the origin unemployment and wage level to be insignificant as has been found frequently in the literature (Greenwood 1997, Lucas 1997). However, we then attempted to isolate two countervailing effects, one a substitution effect among states, and the other a wealth or liquidity effect that allows the worker to cover the fixed cost of moving. The latter effect has been found for unemployment by Goss and Schoening (1984) and Herzog et al. (1993) for the US; they find that the probability of moving decreases with the duration of unemployment. The literature on the wage effect is also extensive (See Stark and Taylor 1991 for a discussion of credit constraints). We generate relative wage (ln wj-ln wi) and relative unemployment (Uj/Ui) variables to capture substitution effects and then allow free standing initial wage and unemployment variables to capture credit constraint effects. In the complete sample, all but the free standing unemployment term enter significantly although it is of predicted 10
However, we have taken a new approach to the question of what the comparison mean should be. We have argued that past debates about whether one should use the mean, median or something else in measuring relative poverty have not made clear the welfare-economic basis for the choice. We have interpreted relative poverty lines in a welfare-consistent way allowing for relative comparisons. The past use of either the mean or median for relativist comparisons in the literature on poverty is then questionable. For example, it does not seem plausible that such comparisons would give the rich either equal weight (as in the mean) or zero weight (the median).

On starting from a model that encompasses a wide range of options, we have found that a rank-weighted mean is more consistent with the data we have assembled on national poverty lines. This implies that one should use a Gini-discounted mean in setting international relative poverty lines. When judged by the fit to national poverty lines, our method provides a marked improvement over past approaches using either the mean or the median. Our results imply that relative-poverty lines should be adjusted downwards in high-inequality countries, but that does not imply less poverty since we also find that a higher share of the mean should be reflected in the poverty line. When compared to half the mean, our proposed relative poverty lines are higher on average and higher for 71% of the countries in our full sample of national poverty lines (77% of the non-OECD sample). Indeed, our relative line is also higher for a majority (60%) of those countries with a Gini coefficient above the median.

The considerable pace of progress against absolute global poverty in the income space that has been documented before in the literature is not found for the weakly relative lines that form our upper bound. But progress is still evident. Our continuously relative measure (updating the line over time as well as across space) shows a declining poverty rate globally. This also holds for all regions, including the high-income countries, though the pace of progress against poverty has been noticeably less in those countries as a whole, and progress against relative poverty in the highincome countries has stalled since the Great Recession. Consistent with the data, our relative poverty lines have a higher elasticity with respect to the mean in richer countries, approaching unity in the richest. So the evident lack of progress against poverty in the rich world implied by our upper bound measures is primarily about the distribution of the gains from economic growth.

Whether one focuses on absolute poverty (our lower bound) or relative poverty (upper bound), the incidence of poverty is appreciably higher in the developing world. Over 90% of the poor by our upper line are found in the developing world, which is home to virtually all of those 32
Grünfeld 2006)<sup>5</sup> . Views on the role of the technology gap for FDI spillovers conflict. Some studies find that a large technology gap is beneficial for local firms since their catching-up potential increases (Findlay 1978; Wang and Blomström 1992; Smeets 2008). Other studies argue that local firms might not be able to absorb positive FDI spillovers if the technology gap between the multinational and local producers is too big or too small (e.g. Blalock and Gertler 2009).

The literature suggests that there is solid evidence for the supportive role of _R&D_ in local firms in high income countries, e.g. Spain (Barrios and Strobl 2002; Barrios, Dimelis, Louri, and Strobl 2004), the US (Keller and Yeaple 2009), Ireland (Barrios et al. 2004), and Sweden (Karpaty and Lundberg 2004), among others. There are also studies confirming the supportive role of R&D in domestic firms for developing or emerging countries, including the Czech Republic (Kinoshita 2001), India (Kanturia 2000, 2001, 2002), Hungary and Slovakia (Damijan, Knell, Majcen, and Rojec 2003), and Indonesia (Blalock and Gertler 2009), among others. One exception is Damijan et al. (2003) finding a negative role of firm-level R&D on FDI spillovers for Estonia and Latvia (reported in Crespo and Fontura 2007).

A domestic firm’s ability to absorb foreign technology might also be positively related to its share of _skilled labor_ . Blalock and Gertler (2009), for example, find that the proportion of employees with college degrees significantly increases domestic firms’ productivity gains from FDI in Indonesian manufacturing. However, Girma and Wakelin (2007) only confirm such a finding for smaller firms in the U.K. – they find that FDI does not affect large firms with a high proportion of human capital, as these firms are probably the most similar to multinationals in terms of technology and market share. In contrast, Sinani and Meyer (2004) find for a sample of Estonian firms that a larger share of human capital reduces the positive spillover effects for domestic firms, but increases it for large firms. Their explanation for this contradicting result is that the competition effect might reduce workers’ possibility to extract additional rents from local firms, since multinationals tend to pay better wages. The competition effect might also enable larger firms to keep skilled workers compared to smaller firms who might lose skilled workers to foreign firms.

_Firm size_ has been positively related to a domestic firm’s capacity to absorb FDI spillovers (e.g. Jordaan 2011b for Mexico). Larger firms may be better positioned to compete with multinationals and to imitate their tools (Crespo and Fontoura 2007). Analogously, larger firms may pay better

> 5 The technology gap is usually measured as a domestic firm’s productivity level relative to a benchmark productivity level within the same sector – often of the leading firms (Griffith, Redding, and Simpson 2002; Girma 2005; Girma and Görg 2007) or of foreign firms (Castellini and Zanfei 2003).

7
3

# **I.   INTRODUCTION**

In part of the economic literature, competitively valued exchange rates are seen as crucial to promote exports (Freund and Pierola, 2012, Di Nino _et al_ . 2012, Eichengreen and Gupta, 2013, Nicita, 2013).<sup>2</sup> However, in the aftermath of the financial crisis, some episodes of large depreciations appeared to have had little impact on exports (e.g. Japan). This has led some observers to question the effectiveness of lower exchange rates (Financial Times, 2015). Are currency depreciations becoming less effective in boosting export growth? What affects the responsiveness of exports to exchange rate changes?

This paper addresses these questions in two steps. First, we analyze how the elasticity of exports to the Real Effective Exchange Rate (REER), a standard synthetic measure of the price competitiveness of countries, has changed over time and across countries and sectors. Second, we study how the formation of Global Value Chains (GVCs) has affected this relationship. Figure 1 focuses on a sample of Central Eastern European countries and provides some suggestive preliminary evidence to motivate our analysis. The figure shows that those countries that are more tightly integrated in German supply chains (Poland, Hungary, Czech Republic and Slovakia) saw a much stronger flattening of the REER growth / export growth to Germany correlation than those that are more loosely integrated in German supply chains (Bulgaria, Latvia, Lithuania, Romania, and Slovenia). While other factors were certainly at play, this evidence suggests that cross-border production linkages may contribute to reducing the effectiveness of depreciations to boost exports.

In our empirical analysis, we use a panel framework covering 46 countries over the period 1996-2012 to formally investigate the questions above. The period of analysis and sample size are determined by the availability of value-added trade data from the OECD-WTO Trade in Value Added (TiVA) database used to assess the role of GVC integration. We focus on manufacturing exports because of the importance of cross-border linkages in this sector. We find evidence that the REER

> 2 See Auboin and Ruta (2013) for a review of the literature on exchange rates and international trade.
# **Table A3. Regression Results for Rainfall Shocks**

``` . regress dlngdp lnrain war ```

|`Source | SS df MS Number of obs = 27`|
|---|
|`-------------+------------------------------ F( 2, 24) = 3.70`|
|`Model | .01452525 2 .007262625 Prob > F = 0.0397`|
|`Residual | .047073279 24 .001961387 R-squared = 0.2358`|
|`-------------+------------------------------ Adj R-squared = 0.1721`|
|`Total | .061598529 26 .002369174 Root MSE = .04429`|
|`-------------------------------------------------------------------------------`<br>`lngdp | Coef. Std. Err. t P>|t| [95% Conf. Interval]`<br>|
|`--------------+----------------------------------------------------------------`<br>`lnrain | .0049515 .0062728 0.79 0.438 -.007995 .017898`|
|`war | -.0492275 .0182825 -2.69 0.013 -.0869607 -.0114942`|
|`_cons | .0177835 .020971 0.85 0.405 -.0254986 .0610655`<br>`-------------------------------------------------------------------------------`|

33
43

# **Glossary**

# **Terms in Respect to the NAFTA Treaty**<sup>**64**</sup>

Described below is each of the major principles and standards used in the NAFTA treaty.

**Sltandard of treatment.** Generally, each NAFTA country must grant "national treatment" and "most-favored-nation" treatment to providers of and investors in financial services from other NAFTA countries. "National treatment" means treatment no less favorable than a NAFTA country accords to its own domestic financial institutions and investors, or their investments, in like circumstances. "Most-favored-nation" treatment means treatment no less favorable than a NAFTA country accords to financial institutions and investors from any NAFTA or non-NAFTA country, or their investments, in like circumstances.

**NMarket Access.** The Agreement requires each NAFTA country to permit individuals and companies from the other NAFTA countries to provide financial services in its territory and to expand throughout its territory, either through separate subsidiaries or direct branches across international boundaries. Each NAFTA country may decide to restrict such access to subsidiaries rather than direct branches. Negotiations to permit direct bank branching across NAFTA country borders will take place if and when the United States allows interstate branching for banks within the United States. In Mexico, access for certain types of financial institutions (e.g., banks, securities firms, insurance companiesj from other NAFTA countries will be subject to market share limitations that will be phased out during a six-year transition period. Mexico has also agreed to permit NAFTA investors that own a bank or securities firm in Mexico to form a financial group that will be eligible to expand into other financial services sectors under Mexican law.

**C"ross-border Financial Services.** Each NAFTA country must permit its citizens and residents to purchase financial services from financial service providers located in the territory of other NAFTA countries. In addition, a NAFTA country may not adopt any new measures restricting cross-border financial services that are permitted by that NAFTA country on the date the NAFTA enters into force, except to the extent set out in that country's reservations to the Financial Services Chapter.

**Rule of Origin.** In general, any citizen, resident or business formed under the laws of a NAFTA country is entitled to enjoy the benefits of the Agreement. This means that financial institutions from outside the NAFTA region may be able to use subsidiaries established in one NAFTA country (such as the United States or Canada) to gain access to another NAFTA country (such as Mexico). However, Canada has reserved the right to deny the benefits of the Agreement to any entity that is not ultimatelv controlled by persons from NAFTA countries.

**64** This material is taken from Bachman (1993) which presents an excellent review of the financial provisions of NAFTA.
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- **Olivetti, Claudia, and Barbara Petrongolo.** 2017. “The Economic Consequences of Family Policies: Lessons from a Century of Legislation in High-Income Countries.” _Journal of Economic Perspectives_ , 31(1): 205–230.

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14
this paper and two research assistants who were trained using the guidelines by Lipsey and Wilson (2001, p.88). Overall intercoder reliability is high and data collection for most of the variables concerning the setting, participants, and research design of the primary studies was straightforward. However, key details of the underlying educational intervention are often missing or underreported in the research reports. If information is only partially missing authors were asked to provide these details via e-mail.

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