rafmacalaba/datause-encoder-data huggingface dataset:
2

# **The** Economic Performance of Senegal, 1960 - 1987

At independence, Senegalese nationals inherited a relatively weliequipped physical and social infrastructure and a GDP per capita that was larger than that of either the Ivory Coast or Cameroon. Over the quarter of a century that followed, however, the economy failed to raise either labor productivity or real per capita incor-e. Official data actually suggest that real GDP per capita decrc .ed by 4 percent between 1967 and 1987,1 while real output per employec and real earnings per employee in manufacturing dropped 31 percent and 33 percent, respectively, - during the 1974 1985 period. As a result, by 1983 Senegal's per capita income of $440 (using the 1987 exchange rate) was barely half that of Cameroon and the Ivory Coast, placing it near the bottom of the ranks of lower middle-income oil importers. The following two sections describe how the structure and growth of gross domestic product changed between 1960 and 1986.

## 2.1 Stricture and Growth of the GDP

Despite certain structural changes, the Senegal economy strongly refects the production patterns established during the colonlial period. As can be seen in Table 2.1, Senegal already had a relativel large secondar and tertiary sector at independence

1. Tbb result i band on calculatons from the foUowing data: current GDP in 1967 205S bilion CFA (Afican Financial r inmunity) Francs, current GDP in 1987 - 1419 bilion CFA Francs, GDP deK i £ in 1967 - 42, GDP deflator in 1987 - 177.6, population In 1967 - 4,117,000, and popuation in 1987 - 6,969,000. Ihe officil data are taken from World Bank (1988 - 89), volume 2, pp. 486-487.

### 2. Seel
4 middle-income countries (Ahmed, Coulibaly, and Zlate 2017; Presbitero 2017; Reinhart, Reinhart, and Rogoff 2012).

Political instability increases risks of economic crises (Bussière and Mulder 2000). Institutional quality helps avoid macroeconomic imbalances and increase resilience of the economies to shocks. This argument has been robustly supported by the literature. Acemoglu et al. (2003) find that countries that inherited more ‘extractive’ institutions from their colonial past were more likely to experience high volatility and economic crises during the postwar period. Dabla-Norris and Gündüz (2014) find institutional quality to be the strongest predictor of a growth crisis. Collier and Goderis (2012) also show that vulnerability to negative shocks is heightened in resource-rich countries with weak institutions, while Elbadawi and Soto (2016) find the vulnerability of oil-rich countries to be conditional on bad political governance.

Low social indicators and high poverty rates do not help such resilience and may mean that an economic crisis of a smaller magnitude results in a reverse graduation because of its larger adverse social impact. Several studies highlight the implications for economic stability arising from households’ vulnerability to poverty as they are less able to cope with economic fluctuations due to limited access to risk-sharing mechanisms and capital markets (Calvo and Dercon 2013; Dercon et al. 2012). Briguglio (2016) stresses the importance of social indicators in economic vulnerability and economic resilience indexes.

# **III IDA Graduation Model**

In this section, we develop a statistical model of IDA graduation.

# _Sample_

Panel data were used for the sample period 1987–2016 to generate predicted probabilities of graduation status. Countries were included only if they had been IDA eligible for at least one year during the sample period and had a population of over 1.5 million.<sup>4</sup> In addition, country-year observations were included only if the GNI per capita for that year was at least 80 percent of the IDA operational cutoff value. As a consequence, this results in an unbalanced sample as not all countries exceeded the threshold for all years. The panel is further unbalanced due to missing data. Table 1 shows the 71 countries that are eligible for the study. Due to the incomplete data set, the final sample had 705 observations from 65 countries. Table 2 presents instances of graduation and reverse graduation in the sample.

> 4 We chose this threshold because countries with population of 1.5 million or less are eligible for IDA credits on most concessional terms defined in IDA’s Small Islands Exception policy. Because of their heightened vulnerability to external shocks and limited economies of scale and scope, small states tend to need concessional financing for longer, so their graduations are usually delayed.
incumbent competitors, our proxy for the ease of entry does indicate that lower ease of entry are conducive to creative destruction, proxied for by firm exit. Put a different way, all else equal, this suggests that in economies with more restrictive barriers, less productive firms are able to persist in the market. We also employ a second measure of new-firm entry, the _de facto_ indicator of the number of new-firm entrants (per 1,000 people), utilizing the running average over the period between survey rounds. Again, we find further evidence that greater new-firm density is correlated with greater likelihood of firm exit, suggesting evidence of creative destruction. This finding backs results such as those in Dunne et al. (1989) and Cable and Schwalbach (1991), both of which report that higher exit rates are likely to be closely correlated with higher entry rates.

Lastly, we find limited evidence of the effect of resolving insolvency on firm exit. We observe sparse – and somewhat counterintuitive – evidence of a negative effect, but only when using our weak definition of exit. This effect indicates that where resolving insolvency is in fact easier, indicated by a higher score on the Doing Business distance to the frontier, is somewhat associated with lower exit rates. This runs counter to the argument that more accommodating insolvency regimes are associated with market conditions, including through the mechanism of new entrants to the market, increasing a firm’s likelihood of exit. Rather, such bankruptcy regimes may be associated with firms being able to weather adverse shocks and remain operating in the market. We only find weak evidence of this effect, and further research would be needed to understand it more completely.

As a robustness check, we estimate the probit equation using country-level, clustered standard errors, which provide a more conservative measure of variance and the results (not reported here) remain the same.

# **V. Conclusion**

Schumpeterian creative destruction, through the churning of the market via the entry of new firms and the exit of less productive ones, has been widely regarded as an economy-wide driver of productivity. While census-based and selective, survey-based efforts have attempted to measure both entry, and to a lesser extent, firm exit, this approach has still not been widely and consistently applied, with the notable exception of some measures of firm entry.

24
**Figure 4. Cumulative spending multiplier +/- 90 confidence intervals. Using spending forecast errors. Increases (** ∆G>0 **) versus decreases (** ∆G<0 **) in spending. OECD countries**

<!-- Start of picture text --> Panel A. ∆G<0 Panel B. ∆G>0<br><!-- End of picture text --> <!-- Start of picture text --> 3 3<br>2 2<br>1 1<br>0 0<br>-1 -1<br>-2 -2<br>0 1 2 3 4 0 1 2 3 4<br>Semester Semester<br>Cumulative multiplier Cumulative multiplier<br><!-- End of picture text -->

**Figure 5. Cumulative spending multiplier +/- 90 confidence intervals. Using spending growth rate. Increases (** ∆G>0 **) versus decreases (** ∆G<0 **) in spending. Developing countries.**

Panel A. ∆G<0 Panel B. ∆G>0 <!-- Start of picture text -->
1.5 1.5<br>1 1<br>0.5 0.5<br>0 0<br>-0.5 -0.5<br>-1 -1<br>0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8<br>Quarter Quarter<br>Cumulative multiplier Cumulative multiplier<br><!-- End of picture text -->
||Domestic<br>impediment|Cross<br>border<br>impediment|food<br>insufficiency.|
|---|---|---|---|
|Domestic<br>impediment|1.0000|||
|Cross border<br>impediment|0.3296|1.0000||
|food<br>insufficiency|0.5428|0.2216|1.0000|

Source: Authors’ calculations Table 6 reports the correlation coefficients between the measure of prevalence of food insufficiency and the indicators of impediments to market integration. First, the indicator of domestic impediments to market integration and the indicator of cross border impediments are positively correlated. This means that countries with relatively low impediments to domestic integration are also, on average, the countries with lowest barriers to integration with neighbors.

Second, the table confirms a negative association between barriers to market integration and food security. For example, the “domestic impediment” index is positively associated with the prevalence of food insufficiency. A positive but lower correlation is found between the food security variable and the impediments to market integration at the border.

Figure 2 shows the relationship between the prevalence of food insufficiency and the estimated impediments to domestic market integration (Figure 2a) and the estimated impediments to cross border market integration (Figure 2b). In both figures there is a positive correlation between prevalence of food insufficiency and levels of domestic and cross border impediments to market integration. In figure 2(a), the countries with the most integrated markets, Djibouti and Malawi, have the lowest levels of food insufficiency. Thus, this provides some evidence that countries in the region with more integrated markets both domestically and internationally have lower problems of food insecurity than less integrated countries: lack of market integration impedes the provision of sufficient amounts of food.<sup>20</sup> <u>Figure 2: Food security and domestic and cross border market integration.</u> (a) Prevalence of food insufficiency and domestic (b) Prevalence of food insufficiency and crossintegration. border integration.

> 20 These simple correlations while illustrative do not reveal causal relationships. There may be omitted variables (such as conflict and the amount of government revenues) which could determine simultaneously both the level of nourishment and the level of market integration.

21
in EUR has been at times 20-60 bps more expensive compared to the USD, but the authorities are willing to pay the extra cost because of the benefits of currency diversification, the access to alternate sources of financing, and the externalities for the corporates willing to fund themselves in EUR.

The benefits of investor diversification proved valuable for the government to meet its funding requirements during the taper tantrum. When tapping the USD market was difficult, Mexico opted for issuing in EUR, finding an appetite for a 30-year bond in 2014 and then a 100-year one in 2015. The 100-year issue was opportunistic: at a time when yields for Germany were negative all the way to the middle sector of the curve, Mexico offered paper that attracted the interest of pension funds and insurance companies hungry for yield.<sup>32</sup>

**Figure 13: Mexico USD and EUR Bond Issuance by Year**

<!-- Start of picture text --> 6000<br>14<br>5000<br>12<br>4000 10<br>BBB+ BBB+<br>BBB<br>8<br>3000<br>6<br>2000<br>4<br>1000<br>2<br>0 0<br>2010 2011 2012 2013 2014 2015 2016 2017<br>EUR USD LT FX Credit Rating<br>Millions USD Eq.<br><!-- End of picture text --> Source: Bloomberg, Standard & Poor’s Diversification is also important because the Mexican government debt is relatively high and rising, and so are the funding needs. Funding USD14 billion in a year in the USD market is not a trivial task and at some point, the large supply may move prices against the issuer. By tapping the EUR market, Mexico makes the funding program in USD more manageable while achieving other objectives. For instance, lowering the issuance in the USD market may help tighten the spreads, helping the sovereign reduce its funding costs.

Accessing the market in EUR has required a sustained effort to “sell” the name to investors and a continued presence in the market. Taking advantage of its BBB+ credit rating, Mexico has conducted regular roadshows and made sure that its securities are integrated in the market indices.

> 32 Similarly, the funding in JPY is more expensive compared to USD but investors are typically buy and hold, giving lower coupons and less volatility to the Mexican securities.

22
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# <u>Results for China</u>

Table 11 shows the results of estimating equation for China. With the exception of the positive effect of **_lccea_** for Electronic Equipment, all estimates have expected signs and are significant for three main industries. Use of email **_lemail_** is significant for all industries. The variables **_compd_** and **_age_** are excluded because their effects were not robust. The lack of significance of **_compd_** may be explained by the argument that the domestic market is so large that the share of an individual firm does not much affect its performance. In the case of **_age,_** we suspect that older firms represent a combination of state firms and former state firms that have been privatized, expanded and modernized, thus the age effect is confounded. In general, labor-related variables are highly significant as are capacity utilization and state ownership. The Chengdu dummy variable is significant and negative in three of the five industry groups, suggesting that there are productivity disadvantages in that city that are not captured by the other regression variables.

**Table 11: Effect of Factors on TFP, China**

||**Apparel**|**Consumer**<br>**Goods**|**Electronic**<br>**Components**|**Electronic**<br>**Equipment**|**Vehicles**<br>**and Parts**|
|---|---|---|---|---|---|
|**Lcaput**|**0.15**|**0.57**|**0.62**|0.02|**0.63**|
||**_2.59_**|**_7.98_**|**_8.64_**|0.33|**_8.72_**|
|**Lccea**|**-0.14**|**-0.26**|0.03|**0.28**|-0.03|
||**_-2.75_**|**_-2.77_**|0.35|**_3.41_**|-0.52|
|**Llostelec**|-0.08|-0.01|**-0.17**|-0.13|-0.06|
||_-1.91_|-0.19|**_-3.91_**|_-1.89_|-1.19|
|**Lemail**|**0.19**|**0.08**|**0.09**|**0.11**|**0.16**|
||**_5.61_**|**2.55**|**_3.07_**|**_3.18_**|**_4.76_**|
|**Leduc**|**1.00**|**0.79**|**1.58**|**2.96**|**1.08**|
||**_3.51_**|**_2.61_**|**_4.98_**|**_6.17_**|**_3.28_**|
|**Stown**|**-0.55**|-0.19|**-0.59**|**-1.03**|**-0.56**|
||**_-6.21_**|-1.49|**_-6.71_**|**_-8.37_**|**_-6.36_**|

18
# Optimal Transition from Coal to Gas and Renewable Power under Capacity Constraints and Adjustment Costs

## Oskar Lecuyer<sup>1</sup> , Adrien Vogt-Schilb<sup>2, 3</sup>

> _1Department of Economics and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland_

> _2The World Bank, Climate Change Group, Washington D.C., USA_

> _3CIRED, Nogent-sur-Marne, France_

_Keywords:_ climate change mitigation; path dependence; optimal timing; investment; resource extraction; dynamic efficiency; early-scrapping; _JEL classification:_ Q54, Q58 Many governments aim at stabilizing climate change to avoid important climate damages, which requires reaching near-zero greenhouse gas (GHG) emissions in the long term (Collins et al., 2013; Steinacher et al., 2013). Abating GHG emissions from power generation is key to reach this goal, as the power sector is currently responsible for nearly 40% of carbon emissions worldwide, and fuel switching to clean electricity is a major technical option to reduce emissions from other sectors (Williams et al., 2012; Kriegler et al., 2014).

Two important features of the electricity sector are that (i) it depends on long-lived capital that in general is tied to a specific fuel, and (ii) today’s power production greatly relies on polluting fossil fuels such as coal (IEA, 2014). Several alternatives are thus available to abate GHG emissions from electricity production. Emissions may be reduced by replacing coal plants with new gas power plants,<sup>1</sup> or with more-expensive but almost-carbon-free options such as renewable power. Also, decision makers can either wait for existing plants to reach their natural lifetime, or decide to decommission them earlier in order to switch faster to cleaner energy sources.

_Email addresses:_ `oskar.lecuyer@vwi.unibe.ch` (Oskar Lecuyer), `avogtschilb@worldbank.org` (Adrien Vogt-Schilb) We thank Mook Bangalore, C ́eline Guivarch, Louis-Ga ̈etan Giraudet, St ́ephane Hallegatte, Jean-Charles Hourcade, Guy Meunier, Jean-Pierre Ponssard, Antonin Pottier, Philippe Quirion, Julie Rozenberg, Fran ̧cois Salani ́e, Ralph Winkler and one anonymous referee from the FAERE Working Paper series for useful comments and suggestions on earlier versions of this paper. We are responsible for all remaining errors. We are grateful to Patrice Dumas for technical support, and to Institut pour la Mobilit ́e Durable (Renault and ParisTech), Ecole<sup> ́</sup> des Ponts ParisTech and EDF R&D for financial support. The views expressed in this paper are the sole responsibility of the authors. They do not necessarily reflect the views of the World Bank, its executive directors, or the countries they represent.

> 1 This paper assumes gas is a low-carbon substitute for coal. The relative carbon content of gas and coal may actually depend on the type of gas and coal and on the particular processes used for extracting and transporting the fuels (e.g., Alvarez et al., 2012). The relative merits of coal and gas also depend on factors disregarded here, such as impact on energy security or impact on local pollution.