rafmacalaba/datause-encoder-data huggingface dataset:
15% in 2035) because most of energy efficiency in the residential buildings in Georgia is expected to occur in the baseline due to existing policies and programs. The potential reductions of GHG emissions in the commercial sector are relatively smaller as compared to that in the residential sector in absolute amount (i.e., million tons). However, in terms of percentage reduction, the commercial sector potential is much higher than that of residential buildings in Georgia thereby implying more space to improve energy efficiency in the commercial and public buildings. Note however that the aggregate emission reduction are, however sensitive to several parameters assumed, such as rate of penetration or adoption of efficient devices and process in the buildings. We have carried out later sensitivity analysis on these parameters.

# **Table 1: Aggregated GHG mitigation potential of energy efficiency measures considered in this study**

||**2020**|**2025**|**2030**|**2035**|
|---|---|---|---|---|
|**(a) Armenia**<br>**Residential Sec**<br>|<br>**tor**||||
|Total GHG emissions from heating, lighting, refrigeration,<br>cooling andTV use (milliontons)|2.96|3.05|3.15|3.23|
|GHG mitigation from the options considered in this study<br>(milliontons)|0.56|0.84|1.12|1.31|
|% reduction of GHG emissions due to the options<br>consideredinthis study|18.9%|27.6%|35.7%|40.5%|
|**Commercial/public**<br>|**Sector**||||
|Total GHG emissions from cooling and street lighting<br>(milliontons)|0.083|0.087|0.091|0.094|
|GHG mitigation from the options considered in this study<br>(milliontons)|0.019|0.024|0.031|0.036|
|% reduction of GHG emissions due to the options<br>consideredinthis study|22.5%|28.1%|33.7%|37.9%|
|**(b) Georgia**<br>**Residential Sec**<br>|<br>**tor**||||
|Total GHG emissions from heating, lighting, refrigeration,<br>TV and washing machine use (million tons)|1.56|2.19|2.9|3.58|
|GHG mitigation from the options considered in this study<br>(million tons)|0.09|0.19|0.35|0.52|
|% reduction of GHG emissions due to the options<br>|5.7%|8.9%|11.9%|14.6%|
|considered in this study|||||
|**Commercial/public**<br>|**Sector**||||
|Total GHG emissions from heating, lighting and street<br>lighting (million tons)|0.24|0.31|0.39|0.45|
|GHG mitigation from the options considered in this study<br>(million tons)|0.04|0.08|0.14|0.20|
|% reduction of GHG emissions due to the options<br>consideredinthis study|16.3%|26.4%|35.9%|43.3%|

13
18

# **References.**

Austen, R. (1987), Africp Economic History: Internal Develogment and External D62endency, London.

Bhatia, R.J. (1985), The West African Monetary Union! An Analytical Review, (Washington, D.C., International Monetary Fund).

Devarajan, S. And J. de Melo (1987), "Evaluating Part_cipation in African Monetary Unions: A Statistical Analysis of the CFA Zones", World Development, Vol 15, No. 4, pp. 483-96.

Devarajan, S. And J. de Melo (1987), "Adjustment with a Fixed Exchange Rate: Cameroon, Cote d;Ivoire and Senegal", The World Bank Economic Review, Vol. 1 No. 3, pp. 447-87.

Dittus, P. (1987), "Structural adjustment in the franc zone - the case of Mali", World Bank CPD Discussion Paper 1987-11.

Guillaumont, P. And S. (1984), Zone franc et develogRement africaine, (Paris, Economica).

Guillaumont, P. And S., eds. (1988), Strateries de developDement comparees: zone franc et hors zone franc, (Paris, Economica).

Guillaumont, P., S. Guillaumont and P. Plane (1988), "Participating in African Monetary Unions: An Alternative Evaluation", World evelopment, Vol 16, No. 5, pp. 569-76.

Honohan, P. (1983), "Measures of Exchange Rate Variability for One Hundred Countries", AiRRied Economics, Vol. 15, pp. 583-602.

Honohan, P. (1990), "Price and Monetary Convergence in Currency Unions: The Franc and Rand Zones", mimeo.

Krumm, K. (1985), "Adjustment policies in the Ivory Coast in the framework of UMOA", World Bark CPD Discussion paper 1985-6.

Krumm, K. L. (1987), "Adjustment in the franc zone: focus on the real exchange rate", World Bank CPD Discussion Paper 1987-7.

Leite and Makonnen (1986), "Savings in the BCEAO countries", Savings and Deve1opment, Vol 10. No. 3, July-September.

Ouattara, A. (1986), "The Balance of Payments Adjustment Process: The Experience of Ivory Coast", Worl DeveloRment.

Yansane, K. (1984?), Controle de l'activite bancaire dans les pays africains de J& zone franc.

- Yeats, A. (1989), "Do African Countries Pay More For Imports? Yes", PPR Working Paper 270.

Yeats, A. (1989), "On the accuracy of economic observations: Do Sub-Saharan Trade Statistics Mean Anything?", PPR Working Paper 307.
is a two-step process. In the first step, (absolute) poverty lines are constructed, often based on minimum levels of calorie requirements. Then in the second step, these poverty lines provide a building block, which is then supplemented with information on the shares of the population defined in relationship to these poverty lines in both periods, to construct vulnerability lines.

Finally, this vulnerability line can offer a lower bound for the middle class. Put differently, it can work as a lower bound value where households with a higher consumption than this line would be considered as belonging to the middle class, and households with a consumption level in between this line and the poverty line belonging to the group that is most vulnerable to poverty.

In terms of estimation, equality (1b) lends itself to straightforward estimation using household panel survey data, where the denominator can be estimated from the cross section in time 0, and the numerator from the panel data spanning both time 0 and time 1. There is no closed-form solution for V0 in equalities (1a) and (1b). However, given household consumption in both periods, the poverty line Z1, and a pre-specified value for either the insecurity or vulnerability index, we can empirically solve for the vulnerability line V0. In particular, since _P_ is a decreasing function of V0, we can iterate from the poverty line upward until we reach a value for V0 that provides the specified vulnerability index. Given appropriate adjustments for inflation rates, the vulnerability line in time 0 can then be updated for later periods just as with poverty lines. In contexts where actual panel data are not available, synthetic panels can be constructed to substitute for such data (Dang, Lanjouw, Luoto, and McKenzie, 2014; Dang and Lanjouw, 2013).

For illustration purposes, Table 1.1 in the Appendix shows the different vulnerability lines that correspond to different vulnerability indexes for India during the period 2004/05- 2009/10. Further examples are provided in Dang and Lanjouw (2014, 2015).

# **III.2. Typology of Poverty and Vulnerability Dynamics**

9
designed to provide information on multiple aspects of living conditions: human capital, productive activities, consumption, and access to and use of public services, _inter alia_ . The survey uses a national probability sample of households stratified by region and urban/rural areas developed to present results at the level of the three ecological zones of the country (GSS, 2006). The survey has been implemented five times in the country since the 1980s with the most recent one carried out in 2005-06.

This last GLSS5 presented us with a significant opportunity. Research experiments are usually constrained by how much information can be collected in one questionnaire. However, by re-visiting a sub-sample of the GLSS5 households, we were able to take advantage of the information already collected. This freed many constraints on the experiment survey. More data could be collected on financial issues in the Financial Service Survey (FSS) as questionnaire space was not needed for gathering data on other characteristics of the household or individuals. Additionally, a more complex design was possible as interviewers only needed to be trained on financial questions and data collection. And, more risks could be taken as the government’s national survey was in no way at risk from the work: the GLSS5 is not a panel survey so any effect of the FSS on households’ willingness to respond to future surveys or specific answers to questions would not be affected by the experimental work.

The original framework for the experiment was a three by two matrix, three types of respondents (head, randomly selected adult and full enumeration) and two types of questionnaires (product-based and institution-based). Designing a survey that would allow all of the potential comparisons and that would isolate the different effects stemming from changing respondents and questionnaire types proved to be too complex 12
particularly true when social insurance programs, even for formal sector workers, do not properly function or provide adequate protection. Self-insurance may be equally difficult regardless of the sector due to credit constraints and myopia. If family members’ vulnerability to risks in the informal sector stems from limited access to social insurance, protection, or information, measures need to be taken to delink social insurance and relevant information from the work sector and expand insurance coverage and accessibility. However, if informal sector is no more vulnerable than formal sector due to other informal safety net, the welfare gain from expanding social insurance may be small.

This paper investigates the informal households’ vulnerability using Yemen’s Household Budget Survey focusing on health.<sup>5</sup> Health is a critical determinant of household well-being, especially in low income countries like Yemen where labor and human capital is usually the main source of income.<sup>6</sup> Using a unique data set that includes information on labor market activities and health variables, this paper investigates whether Yeminis’ health, access to care, and burden of health spending systematically differ by employment sector, and if so, the underlying reasons for these differences. This paper contributes to a better understanding of informality and its implications on household welfare in health in Yemen.

Informality in this study is defined based on access to social insurance.<sup>7</sup> Wage employed workers provided with pension or health insurance or both are formal, whereas workers without access to social insurance coverage are informal. Among the formal wage employed, those with both health and pension coverage are separately categorized with those with pension coverage only, as the role of health insurance in health outcomes is also of interest. Informal workers include the wage

> 5 Ideally, in order to investigated households’ vulnerability to external shock, one needs panel data to track the same individuals or households, showing how their consumption, investment in health and education, or their labor market behavior change in response to the shock. The analysis sets aside these important dimensions of household welfare due to data availability. This area would be a subject for future research.

> 6 Note that Yemen is one of the poorest countries in the Middle East and North Africa Region with about 1,000 dollars GNI(Gross National Income) per capita.

> 7 This is in line with many other studies that defined informality based on protection through social security. See Portes, Blitzner, and Curtis (1986), Marcoullier et al. (1997), and Saavedra and Chong (1999).

3
- [15] Heckman, J. J. (1979). “Sample Selection as a Speci...cation Error,”Econometrica 47(1): 153–161.

- [16] Helpman, E., Melitz, M., and Rubinstein, Y. (2008). “Estimating Trade Flows: Trading Partners and Trading Volumes,”Quarterly Journal of Economics 123(2): 441-487.

- [17] Hillberry, R., and Hummels, D. (2013). “Trade elasticity parameters for a computable general equilibrium model.”Handbook of Computable General Equilibrium Modeling 1: 1213-1269.

- [18] Hummels, D., and Lugovskyy, V. (2006). “Usable Data? Matched Partner Trade Statistics as a Measure of Transportation Costs”Review of International Economics 14(1).

- [19] Javorcik, B. and Narciso, G. (2008). “Di¤erentiated Products and Evasion of Import Tari¤s,”Journal of International Economics 76: 208-222.

- [20] Jiao, Y., and Wei, S. (2020). “Natural Barriers and Policy Barriers,” NBER working paper 28171.

- [21] Kee, H. L., and Nicita, A. (2021). “Discrete Trade Reforms with Heterogeneous Elasticities: Assessing the Impacts of a No-Deal Brexit,”World Bank Policy Research Working Paper 8195.

- [22] Kee, H. L., Nicita, A., and Olarreaga, M. (2008). “Import demand elasticities and trade distortions,”Review of Economics and Statistics 90(4): 666–682.

- [23] Kee, H. L., Nicita, A., and Olarreaga, M. (2009). “Estimating Trade Restrictiveness Indices,”Economic Journal 119: 172–199.

36
Table 3. Bovines, sheep and goats, pigs and poultry numbers for the reference run, by region (billion head). Rosegrant et al., 2009.

|**BOVINES**|**2000**|**2010**|**2020**|**2030**|**2040**|**2050**|
|---|---|---|---|---|---|---|
|**CWANA**|0.124|0.162|0.192|0.218|0.237|0.248|
|**ESAP**|0.578|0.745|0.911|1.055|1.165|1.209|
|**LAC**|0.349|0.430|0.507|0.566|0.610|0.627|
|**NAE**|0.268|0.288|0.306|0.311|0.304|0.282|
|**SSA**|0.179|0.219|0.253|0.273|0.278|0.270|
|**Globe**|1.498|1.844|2.170|2.423|2.593|2.636|
|**SHEEP & GOATS**|**2000**|**2010**|**2020**|**2030**|**2040**|**2050**|
|**CWANA**|0.403|0.491|0.556|0.597|0.614|0.601|
|**ESAP**|0.723|0.871|1.008|1.115|1.184|1.210|
|**LAC**|0.116|0.136|0.154|0.168|0.175|0.174|
|**NAE**|0.195|0.218|0.235|0.244|0.244|0.231|
|**SSA**|0.271|0.346|0.406|0.443|0.459|0.457|
|**Globe**|1.707|2.061|2.359|2.566|2.677|2.673|
|**PIGS**|**2000**|**2010**|**2020**|**2030**|**2040**|**2050**|
|**CWANA**|<0.001|<0.001|<0.001|<0.001|<0.001|<0.001|
|**ESAP**|0.539|0.622|0.669|0.664|0.627|0.558|
|**LAC**|0.080|0.096|0.110|0.119|0.123|0.122|
|**NAE**|0.274|0.295|0.307|0.304|0.290|0.262|
|**SSA**|0.019|0.024|0.029|0.032|0.034|0.034|
|**Globe**|0.912|1.038|1.115|1.121|1.076|0.978|
|**POULTRY**|**2000**|**2010**|**2020**|**2030**|**2040**|**2050**|
|**CWANA**|1.449|1.677|1.901|2.108|2.306|2.424|
|**ESAP**|7.478|10.112|12.979|15.712|18.168|19.687|
|**LAC**|2.286|2.893|3.531|4.151|4.762|5.245|
|**NAE**|4.180|4.677|5.180|5.542|5.780|5.750|
|**SSA**|0.784|0.991|1.170|1.306|1.407|1.445|
|**Globe**|16.178|20.350|24.760|28.819|32.423|34.551|

CWANA Central and West Asia and North Africa ESAP East and South Asia and the Pacific LAC Latin America and the Caribbean NAE North America and Europe SSA Sub-Saharan Africa 18
54 indirect tests that don't shed much light on the issue of trade regimes. The problem is mainly one of measurement. These studies have not been able to construct a convincing objective and continuous index of trade intervention.

In Section V we derived a modified neoclassical growth model and presented new cross section results that do use an index of intervention that satisfies most of the requirements discussed in Sections II and III. The model is based on Arthur Lewis' proposition that a more open economy and less distorted trade regime will result in a faster rate of absorption of technological progress origincting in the advanced countries. The model is very simple and uses an aggregative neoclassical framework to analyze the out of steady state relation between trade intervention and growth. The empirical analysis ui d a 30 country cross section data set. The results obtained provided strong support for the model indicating that, after controlling for the relevant variables, a higher degree of trade intervention will imply a decline in the rate of growth of output.

Although these results are very encouraging, there are a number of unresolved issues that chould be tackled by future research. First, more detailed micromodels of the process of technology absorption should be explored. Second, the search for an even better index of intervention should continue.
# **2 THEORETICAL MODELS AND POLICY IMPLICATIONS**

For the purpose of our discussion, we classify the different theoretical frameworks in which internal migration has been modeled into three types: the first type covers the dual economy models which emerged in the 1950s and 1960s, the second type covers the Harris-Todaro models developed in the 1970s and 1980s, and the third type covers the more elaborate microeconomic models on which much of the research has focused over the past 15 years (including some important contributions to the so-called New Economics of Labor Migration).<sup>3</sup> We will survey these families of models and their policy implications sequentially.

## _2.1 The beneficial role of migration in early dual economy models_

The first theoretical work involving rural to urban migration is the Lewis (1954) model of development which tries to explain the transition from a stagnating economy based on a traditional rural sector to a growing economy driven by the development of a modern urban sector. In this model, economic growth does not only stem from the accumulation of capital in modern industry but also from the _interaction_ between the rural and the urban sectors. Lewis assumes that rural economies initially present a specific context in which there is ‘surplus labor’ in the agricultural sector, so that marginal productivity in that sector is close to zero. Workers in the rural sector are assumed to share the output among themselves so that they are remunerated at their mean product.<sup>4</sup> Given these assumptions, the agricultural sector is able to supply a perfectly elastic labor force to the modern industrial sector which can grow by accumulating capital and poaching labor from the traditional agricultural sector, paying wages just equal to the mean product in the agricultural sector. The transfer of the labor force between the two economic sectors involves the reallocation of the labor force across space through migration from low population density rural to high population density urban areas. Migration occurs until surplus labor or ‘disguised unemployment’ is absorbed by the modern sector. Ranis and

> 3 For a presentation of the New Economics of Migration and its research program, see Stark (1991). For a mostly empirical survey on internal migration in developing countries, see Lucas (1997). 4 The reason for this payment arrangement is to avoid having workers paid a wage equal to zero as would imply marginal productivity remuneration under surplus labor.

8
**Table 1. 1  Average number of accounts per type of institution and deposit level**

||**COP 1-5**<br>**million **|**COP 5-10**<br>**million**|**COP 10-20**<br>**million**|**COP 20-50**<br>**million**|**COP 50-100**<br>**million **|**Over COP100**<br>**million**|
|---|---|---|---|---|---|---|
|**CURRENT ACCOUNTS**|||||||
|Private Domestic Banks|59,191|2,629|1,851|1,459|576|612|
|Private Foreign Banks|43,385|1,677|1,079|782|277|279|
|Public Banks|172,102|3,495|2,552|2,178|907|1,071|
|Total current accounts|65,967|2,423|1,684|1,323|518|556|
|**SAVINGS ACCOUNTS**|||||||
|Private Domestic Banks|1,029,685|15,647|8,365|4,305|948|711|
|Private Foreign Banks|247,421|2,963|1,878|1,022|239|234|
|Public Banks|172,102|3,495|2,552|2,178|907|1,071|
|Total savings accounts|698,198|10,453|5,750|3,066|724|601|

_Source: Own calculations based on Superintendencia Bancaria data_ 21. An analysis of average savings amounts shows that the average savings amount with credit institutions (banks) is about COP306,700 (US$119<sup>17</sup> ) in the smallest range. This suggests that small savers have a savings capacity of about one minimum salary<sup>18</sup> . Higher average savings amounts for other financial intermediaries are explained by their regulatory restrictions on taking savings deposits. These numbers also show that average savings levels by lower-end clients do not significantly exceed minimum account opening or balance requirements by banks (see Chapter 2).

**Table 1. 2  Average size of deposit amounts in active savings accounts**

|COP million|Less than $5|$5 -$10|$10 -$20|$20 -$50|$50-$100|Over $100|
|---|---|---|---|---|---|---|
|Credit institutions|306,639|6,576,824|12,986,545|27,912,260|55,450,203|1,041,420,302|
|Financial<br>corporations|701,846|8,214,000|15,426,750|20,255,000|68,123,000|3,977,280,081|
|Commercial<br>finance companies|768,236|6,939,667|14,337,250|32,820,500|83,057,000|824,328,000|
|Financial<br>cooperatives<br>**_Total active accts_**|429,409<br>**_306,791_**|6,775,080<br>**_6,577,066_**|13,558,793<br>**_12,987,120_**|27,872,800<br>**_27,912,376_**|68,375,462<br>**_55,461,244_**|242,573,867<br>**_1,042,339,394_**|

_Source: Own calculations based on Superintendencia Bancaria data Note: Inactive accounts are those which have not been used in the past six months_ 22. **Following the banking crisis, the relative supply of loan services has changed.** The total amount of gross loans in the period 1998-2003 has remained flat at around COP53 trillion. However, commercial loans increased by 18% over this period and now account for over 60% of available credit. In contrast, mortgage loans suffered a reduction of 38% between 1998-2003. The decline in mortgage lending is a direct result of the crisis, as asset problems in the mortgage sector and the closing of

- 17 Exchange rate of 1US$ = COP2,585 (as of October 27, 2004).

> 18 Minimum monthly salary in Colombia for year 2004 is COP358,000, or US$138.

25
# **Fragmentation, Incomes, and Jobs: An Analysis of European Competitiveness**

Marcel P. Timmer<sup>a,</sup> * Bart Los<sup>a</sup>

## Robert Stehrer<sup>b</sup> Gaaitzen de Vries<sup>a</sup>

**JEL Codes** : F6, J2, O47, O57

**Keywords** : Global value chains, fragmentation, competitiveness, specialisation **Sector Board** : Economic Policy

### **Affiliations**

a Groningen Growth and Development Centre, Faculty of Economics and Business, University of Groningen b The Vienna Institute for International Economic Studies (WIIW)

### *** Corresponding Author**

Marcel P. Timmer Groningen Growth and Development Centre, Faculty of Economics and Business University of Groningen, The Netherlands, m.p.timmer@rug.nl