rafmacalaba/datause-encoder-data huggingface dataset:
Policy Research Working Paper 9196

# **Abstract**

This paper assesses the impact of Internet job search on employment in the Arab Republic of Egypt, the most populous country in the Middle East and North Africa region. Using panel data from the 2012 and 2018 rounds of the Egypt Labor Market Panel Survey, the paper examines the impact of Internet job search by the unemployed on their employment prospects. It also examines the impact of Internet job search by employed job seekers on their wage growth, as well as the impact of digitalization at the workplace on earnings. Accounting for individual and geographical unobserved heterogeneity using panel data, the results suggest that Internet job search is an effective job search method, as it increases the probability that the unemployed—and in particular unemployed men—will find employment. Auxiliary placebo regressions confirm that preexisting trends in labor market outcomes are not driving the results. However, Internet job search by employed job seekers does not appear to have an impact on their wage growth, nor does digitalization at the workplace affect the wage growth of employed individuals.

This paper is a product of the Office of the Chief Economist, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at nelly.elmallakh@psemail.eu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **HI. GLOBAL TIMBER TRADE PATTERNS AND REVENUES**

Timber certification most likely will have its initial impact on that portion of the tropical timber produced that enters trade and that is imported by those countries that have been involved in developing norms and guidelines noted in the previous section. It is therefore crucial to understand the dynamics of the tropical timber trade and more specifically, the particular producing countries and quantity of timber that could potentially be affected by certification.

While TC is intended to apply to all types of timber, the focus of this paper is on **tropical** timber products, excluding fuelwood. Hence, the figures presented will focus on the tropical timber trade. The FAO timber statistics used do not distinguish between tropical and nontropical timber. The distinction is between non-coniferous (temperate and tropical together) and coniferous. With certain exceptions, the non-coniferous timber production of developing countries can be classified under tropical. Major exceptions are China, Argentina, Chile and the Near East. These are relatively large producers residing in the temperate zone. While some other developing countries located in temperate areas are still included in our data, their magnitude in both trade and production values and volumes are not significant to distort the analysis.

**Table 1: Production and Exports of Timber Products in Developing Countries, 1991**

|Product|Export<br>Volume<br>(in 1,000 cubic meters)|Export Value<br>in million US$|
|---|---|---|
|Logs (NC)|25,868|2,420<br>|
|Sawnwood (NC)|8,919<br>|2,285<br>|
|Wood-based panels|12,652|4,318|
|Total||9,023|

Source: WorldBank,IECrT, CalculationsbasedonFAO, _ForestProducts Yearbook_ (1991) data.

Notes: (i) NC signifies non-coniferous; (ii) Wood-based panels are mainly veneer and plywood, but also Include particle board and fiberboard.

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share of oil in total exports (to capture potential the potential impact of Nigeria’s oil wealth on its import composition) as well as the applicable tariff rate. We built a dataset with this information from the TRAINS database (for import shares and tariffs) and World Development Indicators (all other variables) for all countries with available data. Then, we estimated the model separately for each product over the cross country sample and obtained the coefficients that then enable us to predict the import share of each product given a countries characteristics and tariff on the product. We use this approach to predict the “typical” amount of Nigerian imports or each product if the bans were to be removed and replaced by a tariff. While this approach is rather ad hoc it does provide transparent estimates from a simple approach. These estimates should be interpreted seen as orders of magnitude rather than well founded predictions.

# **Table 9. Observed imports under ban categories and indicative import response to replacing the** **<u>import bans with a 35 percent tariff rate, 2006, Top 20 Most affected categories, US$ million</u>**

|Bancategory|Observed<br>imports|Predicted<br>imports|Response<br>to lifting<br>the ban|
|---|---|---|---|
|**Total **|**1,828**|**4,236**|**2,408**|
|39 - Used Motor Vehicles above eight (8) years from the year of<br>manufacture|402|903|501|
|20–Medicaments|361|739|379|
|32 - Africanprintfabrics, Carpets,LaceFabrics,Towels|409|719|309|
|33– Yarn|15|277|262|
|9- Vegetable Oils andFats|9|242|233|
|7 - Maize,Millet, Sorghum|4|168|164|
|8- WheatFlour,MaizeFlour, CerealGroats,MealandPallets|4|127|123|
|2 – Pork and Pork Products, Beef and Beef Products, Mutton, Lamb<br>and GoatMeat|3|87|83|
|1 – Live or DeadBirdsincludingFrozen Poultry|1|84|83|
|42 – Furniture|28|64|36|
|27–Toothpicks|18|52|33|
|38-UsedAir-Conditioners, Compressors andFridges/Freezers|130|160|31|
|6- FreshandDriedFruits|2|27|25|
|35- FootWears andBagsincluding Suitcases of leatherand plastics|76|95|19|
|17 - Beer[Bottled, Canned orotherwisePacked]|2|20|17|
|23- Finished Soaps|39|56|16|
|24-Disinfectant, Germicides, Mosquito repellents|26|42|16|
|34 - ExerciseBooks|0|14|13|
|40- Fully built and CKD BicyclesFrames,Forks andMudguards|15|24|9|
|3- BirdsEggs|2|10|8|

Source: Computed by authors 21
new population, no land decrease for reduced population' should be continued." At the end of 1997, the party committee issued another document stipulating that "the contract term of arable land be extended for another 50 years (compared to 30 years nationally), and the term for non-arable land for another 60 years, both starting with 1994." This policy has been widely implemented by giving farmers certificates to the land they cultivate.

Guizhou's early implementation of a policy that exogenously provides significantly longer and more secure land rights than was available to farmers in other areas of China provides an ideal case to assess the impact of such policies in comparison to other provinces. To explore this issue, we rely on a household survey that covered 1001 households from 110 villages in Guizhou, western Hunan, and Yunnan provinces. These provinces were chosen on the basis of their proximity and climatic and geographic similarity to Guizhou. The expectation was that farmers outside Guizhou would enjoy lower levels of tenure security than those within Guizhou. Comparing the impact of property rights arrangements in Guizhou, either directly through a variable indicating whether village leaders were aware of the adoption of the "two nos" policy, or indirectly through a provincial dummy, to those in other provinces, provides a mechanism to ascertain the impact of the policy on the vanables of interest. In addition to the "two nos" policy, we add information on two other interventions in the sphere of property rights. One refers to villager perception of the transferability of land nghts within the village, an indicator that is justified in view of recent evidence suggesting the importance of transferable land nghts (Carter and Yao, 1999). A second indicator is whether villagers have received written land use certificates. Before describing the data.in more detail, we discuss the research questions to be addressed.

# 2.3 **Research questions**

We intend to use these data to address three main questions, namely: (i)' whether changed land tenure arrangements had an appreciable effect on agricultural investment; (ii) whether land policy had a negative impact on equity and/or affected households' ability to cope with shocks, thereby causing a reduction in their ability to invest in physical and human capital or to access land, and; **(iii)** what determines households' preferences for specific land rights. The justification for each of these questions and their relation to the existing literature is discussed below.

_Agricultural investment.-_ A number of studies from China suggest that tenure insecurity may have affected economic outcomes in three ways. First, insecure tenure was found to prevent much needed investment in land improvement (Jacoby, Li, and Rozelle, 2001), something that may have had

> l Note that these were not randonized expenments and that no systematic evaluation of the impact was undertaken.

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_CHAPTER 6. UNIT LEVEL MODELS: GENERAL INDICATORS_ 49 as a fixed census and rawing 500 samples from it using a realistic sampling method. In these simulation experiments, the CEB estimates were practically identical to EB ones, and both performed generally better, in terms of MSE, than the traditional ELL.

As the EBLUP, neither the original ELL estimators, nor the EB or the Census EB estimators based on the nested error model, account for the sampling design, and might be biased under informative sampling. Similar to the Pseudo EBLUP of You and Rao (2002a), Guadarrama, Molina and Rao (2014) defined Pseudo EB predictors that incorporate the survey weights in the EB procedure. They noticed that the conditional distribution (6.9) defining the EB predictor under the homoscedastic nested error model (5.1) with _kdi_ = 1 for all _i_ and _d_ , depends on the sample data **y** _ds_ only through the (unweighted) area sample mean _y_ ̄ _d_ , that is, _δ_ ˆ _d_<sup>_EB_</sup> = _E_ **y** _dr_ ( _δd|y_ ̄ _d_ ). Then they defined the Pseudo EB predictor of _δd_ as _δ_ ˆ _d_<sup>_PEB_</sup> = _E_ **y** _dr_ ( _δd|y_ ̄ _dw_ ), where the expectation is now taken with respect to the distribution of out-of-sample units, given the weighted area means ̄ _ydw_ . The resulting conditional distribution, for each out-of-sample unit _ydi_ , _i ∈ rd_ , is now

where the conditional mean and variance are given by for _γdw_ defined in (5.9). Guadarrama, Molina and Rao (2014) adapted the Monte Carlo simulation procedure for EB estimation to the Pseudo EB and proposed a parametric bootstrap procedure to estimate the MSE of the Pseudo EB predictor. A Census version of the Pseudo EB predictor, similar to the Census EB, can be easily defined.

For an area mean _Y_<sup> ̄</sup> _d_ , the Pseudo EB reduces to the Pseudo EBLUP of You and Rao (2002a) given in (5.9), when using the same estimators of
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# **I. Introduction**

As noted by the International Panel on Climate Change (IPCC, 2001b), climate change will have many negative effects, including greater frequency of heat waves; increased intensity of storms, floods and droughts; rising sea levels; a more rapid spread of disease; and loss of biodiversity. Sea level rise (SLR) poses a particular threat to countries with heavy concentrations of population and economic activity in coastal regions.

Until recently, studies of SLR typically predicted a 0-1 meter rise during the 21<sup>st</sup> century (Church et al. 2001, IPCC Third Assessment, 2001). The three primary contributing factors have been cited as: (i) ocean thermal expansion; (ii) glacial melt from Greenland and Antarctica (plus a smaller contribution from other ice sheets); and (iii) change in terrestrial storage. Among these, ocean thermal expansion was expected to be the dominating factor behind the rise in sea level. However, new data on rates of deglaciation in Greenland and Antarctica suggest greater significance for glacial melt, and a possible revision of the upper-bound estimate for SLR in this century. Since the Greenland and Antarctic ice sheets contain enough water to raise the sea level by almost 70 m (Table 1), small changes in their volume would have a significant effect.<sup>1</sup>

**Table 1** : Physical characteristics of ice on Earth.

||**Glaciers**|**Ice caps**|**Glaciers and**<br>**ice caps ***|**Greenland**<br>**ice sheet**|**Antarctic ice**<br>**sheet**|
|---|---|---|---|---|---|
|Number<br><br>|> 160,000|70||||
|Area (10<br>6km<br>2)<br><br>|0.43|0.24|0.68|1.71|12.37|
|Volume (10<br>6km<br>3)|0.08|0.10|0.18 ± 0.04|2.85|25.71|
|Sea-level rise equivalent (m)|0.24|0.27|0.50 ± 0.10|7.2|61.1|
|Accumulation<br>(sea-level equivalent,mm/yr)|||1.9 ± 0.3|1.4 ± 0.1|5.1 ± 0.2|

Source: Church _et al_ . (2001), Table 11.3 Data sources: Meier and Bahr (1996), Warrick _et al_ . (1996), Reeh _et al_ . (1999), Huybrechts _et al_ . (2000). * - does not include Greenland and Antarctic ice sheets (represented in the next columns) Since the IPCC Third Assessment Report in 2001, there has been an increased effort to improve measures of mass loss for the Greenland ice sheet and its contribution to SLR. Using satellite interferometry observations, Ringot and Kanagaratnam (2006) detected widespread glacier flow acceleration in the lower latitudes between 1996 and 2000, and rapid extension to higher latitudes by 2005. When combined with surface loss estimates

> 1 If the Greenland ice sheet were to melt completely, it would raise average sea level by approximately 7 meters (Church et al. 2001).

3
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# **Table 4**

**Severance pay by employee and job characteristics**

||**Legally entitled**<br>**severance pay**<br>**amount**<br>**IDRs(million)**|**Actual**<br>**severance pay**<br>**received**<br>**IDRs(million)**|**Ratio of actual**<br>**amount received to**<br>**legally entitled**<br>**severancea**|
|---|---|---|---|
||||**py**|
|**Age**||||
|15–18 years|1.279|0.087|6.8%|
|19–24 years|2.729|0.211|7.7%|
|25–34 years|7.958|2.527|31.8%|
|35–49 years|15.512|6.181|39.9%|
|50–64 years|21.399|2.302|10.8%|
|65 years and older|7.883|0.329|4.2%|
|All ages|8.264|2.410|29.2%|
|**Gender**||||
|Female|5.751|2.047|35.6%|
|Male|9.719|2.622|27.0%|
|**Education**||||
|Less than primary|8.676|2.574|29.7%|
|Primary|5.964|1.555|26.1%|
|Junior secondary|8.573|2.065|24.1%|
|Senior secondary|8.477|2.931|34.6%|
|Tertiary|13.156|5.688|43.2%|
|**Industry**||||
|Agriculture|8.520|0.835|9.8%|
|Mining and quarrying|2.200|0.000|0.0%|
|Manufacturing|7.842|2.872|36.3%|
|Utilities|N/A|N/A|N/A|
|Construction|7.101|2.873|40.5%|
|Trade|10.928|3.544|32.4%|
|Transportation|11.874|4.719|39.7%|
Figure 4. Generation of power, by fuel (1990-2014) <!-- Start of picture text --> 200,000 0.70<br>180,000<br>0.60<br>160,000<br>140,000 0.50<br>120,000 0.40<br>100,000<br>0.30<br>80,000<br>60,000 0.20<br>40,000<br>0.10<br>20,000<br>0 0.00<br>Hydro Geothermal Other renewables<br>Coal Oil Gas<br>Biofuels and waste Nuclear Total final consumption<br>Fuel type concentration index<br>GWH<br><!-- End of picture text --> Source: IEA, 2015

# _Institutions_

In general, planning and procurement of generation and transmission in the Egyptian power sector are conducted by the Ministry of Energy, EEHC, and EETC, in close coordination and reasonably in advance of the new assets being needed by the power system. The power sector saw several new laws and policies put into place in 2015 and the country is transitioning to this new framework currently. Since 2000, generation planning was done by the EEHC and the transmission planning was done by EETC. Once the plans were submitted to and approved by the Ministry of Electricity and Renewable Energy, they were presented to the cabinet of the ministers for approval and allocation of the necessary financial resources for the execution of the plan. However, the new electricity law in 2015, Law 87, assigned the planning task to the EETC (functioning post 2015 as a TSO) jointly with the Ministry of Electricity and Renewable Energy, allowing for three transitional years. The plan will be more or less indicative, with an annual report for adequacy of generation issued by the EETC and reviewed by the regulatory agency- EgyptERA. The regulator will then report to the cabinet of ministers and make suggestions to overcome any challenge to the security of supply.

Most procurement has of course been conducted for public sector projects (with the exception of the brief burst of IPP procurement 20 years ago, and the recent rounds of renewable energy generation procurements), as EPC contracts on a competitive basis (usually with a high degree of transparency, particularly for projects with development partner financing). As of 2015, the procurement was carried out based on the five-year generation or transmission plans. The respective generation or transmission companies raise funds locally and globally (mostly through IFIs such as World Bank, EBRD, AfDB etc.). Once financing is in place, the project equipment, engineering and construction services are procured through 13
**Figure 1:** Real GDP growth and GDP per capita, 1962-2007

<!-- Start of picture text --> 25% 180<br>Real GDP growth rate<br>(LHS)<br>GDP per capita (RHS) 160<br>20%<br>140<br>15%<br>120<br>10%<br>100<br>80<br>5%<br>60<br>0%<br>40<br>-5%<br>20<br>-10% 0<br>Source : WDI<br>Constant 2000 USD<br>1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 2 198 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006<br><!-- End of picture text --> Burundi is a rural economy, which is dominated by agriculture with food crops as the main driver of growth. The low productivity of the agriculture sector, however, hampers its contribution. The secondary sector is the smallest sector, but its contribution is increasing. Especially the construction sector has been on the rise fueled by high aid inflows and the resulting increase in imports. The share of the services sector is increasing, reflecting a continuous increase in public services rather than the expansion of the private services.

Burundi has a very narrow export base, with exports averaging less than 10 percent of GDP over the last 10 years. The main export crops are coffee and tea, with coffee accounting for about two thirds of the export value. Imports, on the other hand, are increasing, mainly financed by the increasing level of foreign aid. Consequently, the current account deficit has been rising and Burundi remains dependent on foreign aid in the foreseeable future.

Investment levels are still low, but have recorded an upward trend, averaging 16 percent of GDP in 2005-2008, almost double the average of 2001-2004. The recovery of private investment is especially noteworthy, having risen from a very low base in 2001 (2.2 percent of GDP) to 9.2 percent of GDP in 2008. The very low level of foreign direct investment, on average less than 1 percent of GDP over the last 10 years, is an additional contributing factor to the low overall investment level and a sign that the investment climate is not attractive for foreign investors (perception of insecurity, political instability, and business environment).

# **3. Burundi’s policy response to increased aid flows**

# 3.1. <u>The impact of increased aid flows – analytical framework</u>

While a country can greatly benefit from increased levels of aid to finance needed projects and programs, additional external assistance can also have negative effects on the real exchange rate, exports and competitiveness. The impact of an increase in aid, however, depends to a large extent 5
This paper in similar in spirit to Reinhart and Rogoff (2008). They examine previous financial crises for information on the macroeconomic implications of the current crisis. They find that banking crises are associated with severe declines in asset prices, output, and employment—though the decline in output tends to be relatively less protracted as compared with asset prices and employment. They also find that government debt balloons as a result of collapsing tax revenues and countercyclical policies. While our focus on global downturns and international trade is quite different from theirs, there is one important similarity in our results. Our results point to a sharp but relatively short-lived decline in trade, akin to what they find for output. A significant difference is that unlike the expanding government debt they observe, we find that international borrowers often reduce international debt following global downturns.

# **II.  Methodology**

Following Milessi-Ferretti and Razin (1998) and Freund (2005) on current account reversals, we use a filter to identify episodes of global downturns. Specifically, a global downturn must satisfy the following criteria:

- (a) World real GDP growth below 2 percent.

- (b) A drop of more than 1.5 percentage points in world real GDP growth from previous 5 year average to current rate.

- (c) Considering the previous 2 years and the following 2 years, growth is at a minimum.

The first two conditions ensure growth is low and has dropped sharply. If the first two conditions identify consecutive years, i.e. prolonged recessions, the final condition chooses the minimum growth rate as the event year. Using data on real GPD (in constant 4