rafmacalaba/datause-encoder-data huggingface dataset:
**Total factor productivity (TFP)** growth, averaged 1.4% over 2001‐2010 based on calculations by The Conference Board (2018). Our own estimations following the methodology in Kim and Loayza (2019) also suggest an average growth rate of 1.4% for the same period.<sup>13</sup> See Graph 6.

**<u>Graph 6: Pre‐Conflict Total Factor Productivity (TFP) Growth</u>**

<!-- Start of picture text --> %<br>8.0<br>6.0<br>4.0 1.4<br>2.0<br>0.0<br>‐2.0<br>‐4.0 1.4<br>‐6.0<br>‐8.0<br>Kim and Loayza methodology (KL) (2019) The Conference Board (TCB) (2018)<br>KL (2019), average 2001‐2010 TCB (2018), average 2001‐2010<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010<br><!-- End of picture text -->

# **2.2 Simulation of what would have happened in the absence of conflict**

Table 1 details the baseline calibration of the LTGM‐PC for simulation under the no‐conflict scenario. The baseline assumptions are consistent with a long‐term GDP growth average of close to 5.0%. Average real GDP growth of 5.3% over 2011‐2018 would have led to real GDP rising from USD 60 billion in 2010 to USD 91 billion, and real GDP per capita rising from USD 2,857 to USD 3,774 by 2018. We discuss the baseline assumptions in sub‐sections 2.2.1 ‐ 2.2.2 below. Sub‐section 2.2.3 considers upper and lower estimates for the calibration.

## _2.2.1 Key parameters and initial conditions_

Key parameters and initial conditions (panels A and B of Table 1) either take their 2010 values or are calibrated. In panel A of Table 1, Syria’s share of labor income of 0.520 is proxied by the 2010 average value for relatively conflict‐free middle‐income MENA economies from PWT 9. This value is close to the average for lower‐middle income (LMI) countries (0.510), as well as “oil‐based” middle‐income economies with fuel exports amounting to less than 60% of their merchandise exports (0.540). The Conference Board (2018) also uses a similar value of 0.500. We calibrate the depreciation rate for aggregate capital to 4.8%, which is the PWT 8.1 data point for 2010 (PWT 9 gives a value of 5.5% for the same year). Generally, for Syria, PWT data suggests a relatively low share of structures (compared to other forms of physical capital) and hence a high depreciation rate, one that is above the MENA and LMI averages. So, we choose the lower of the two PWT depreciation values given the possibility of measurement error. The public capital depreciation rate of 3.1% follows the PWT 9 depreciation rate for non‐residential structures. Calculated as a residual, the private capital depreciation rate of

> 13 TFP is measured using growth accounting based on the standard Solow‐Swan growth model with human capital. Syria data for output, physical capital, human capital, and employed persons are taken from Penn World Tables (PWT) 9. Labor share is proxied by the average for four relatively conflict‐free middle‐income Middle East and North Africa (MENA) economies (Djibouti, Jordan, Morocco and Tunisia).

8
depend on such characteristics. In this case, the relationship between bribe payments and profitability will also be positive. Although the basic ingredient in both the 'speed money' and the endogenous harassment theories is that the bribe amount of different firms increase with the willingness-to-pay for service, the utility employees demanding the bribe need more information in the 'endogenous harassment' theory. In the "speed money" hypothesis the enterprise paying the bribe self-selects the amount of the bribe according to its cost of waiting, while the endogenous harassment version requires that the utility employees taking the bribe discriminate between enterprises and, thus, require that the utility has information on profitability and other firm characteristics that affect the enterprises' willingness-to-pay. In practice, the data used in this paper do not allow us to easily distinguish between these two theories.

Related to the endogenous harassment theory, another factor that might affect enterprises' willingness-to-bribe is size of the enterprises' overdue payments to the utility company - something that is a significant problem in many countries in Eastern Europe and Central Asia.'3 When an enterprise had high debts to the utility company, the utility employee can more credibly threaten to cut the enterprises' utility connection - the enterprise manager would find it more difficult to complain to either the judiciary or to the employee's superiors within the utility company about being disconnected if he has overdue payments. In bilateral bargaining between the utility employee and the firm, the fallback position of the firm is worse and, hence, its bargaining power is weaker. Consequently, the utility employee will be able to extract higher bribes from firms that have overdue payments to the utility. In contrast, overdue payments to workers or suppliers should not have this effect - although the utility employee would be able to threaten to cut off service to a non-paying customer, it would not be able to do the same to a customer that pays its utility bills in a timely way but has overdue payments to suppliers or employees. Further, to the extent that overdue payments suggest that the enterprise is distressed or has cash flow problems, we might expect enterprises with other types of overdue payments to be less willing (or able) to pay cash bribes. Since several authors have argued that overdue payments to workers are a better measure of financial distress than overdue payments to suppliers, we might expect enterprises with overdue

> 13 In the World Business Environment Survey (WBES) for the transition economies, 33 percent of enterprises reported having overdue payments to utilities. For a general discussion of non-payment in the power sector in Eastern Europe and Central Asia, see World Bank (1999).

7
<!-- Start of picture text --> % graduate degree % women out of labor force<br>re) ~<br>oo<br>+ S<br>oy 2<br>2 ¥<br>‘©NN Eefe}<br>8S<br>@5<br>2=<br>8°o<br>8 8<br>@o et<br>B o<br>=] ~<br>3 3<br>oa” S<br>2 E<br>20<br>x<br>1960 1970 1980 1990 2000 2010 1960 1970 1980 1990 2000 2010<br>excludes outside values excludes outside values<br><!-- End of picture text -->
POLICY RESEARCH WORKING PAPER 1656

# Summary findings

In the United States, gross business investments in plant and equipment (fixed investments) constitute only about 10 percent of GNP, but such investments may represent GNP's most important component because (1) plant and equipment have a long-term effect on the economy's productive capacity, (2) changes in investment spending directly affect levels of employment and workers' incomes in durable goods industries, and (3) supply and demand are sensitive to changes in investment, which is the most volatile component of GNP.

Economists have long been concerned about what - in the economy, the industry, and the firm - determines investments in capital spending. Using a panel of data for U.S. manufacturing firms for 1972-90, Samuel compares five theories of investment: accelerator theory, cash flow theory (liquidity model, managerial model, and information-theoretic model), neoclassical theory, modified neoclassical (Bischoff) theory, and Q theory.

If the results from cross-section regressions can be viewed as representing the long-term equilibrium, the single most important determinant of capital spending appears to be cash flow.

Apparently, managers care more about cash flow and cost of capital than about stock market signals and the level of output. And at the firm level, managerial perceptions about fundamentals are more important than market perceptions. For managers, the stock market may be a side show to capital spending decisions.

To generalize in a way that might be useful for developing countries: Financial decisions at the firm level are closely linked to real decisions in the economy. Internal finance is the most important source of funds, and capital spending is the most important use of funds, so there is a close relationship betwen real and financial decisions.

This paper - a product of the Operations Policy Group, Operations Policy Department - is part of a larger effort in the department to disseminate results of policy analysis. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Cherian Samuel, room MC10-362, telephone 202-473-0802, fax 202522-3253, Internet address csamuel@worldbank.org. September 1996. (51 pages) _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 used and cited accordingly. The findings, interpretations, and conclusions are the authors' own and should not be attributed to the World Bank, its Executive Board of Directors, or any of its member countries._ Produced by the Policy Research Dissemination Center
enforcement and the treatment of creditors and shareholders are influenced by the origin of legal code. More specifically, they find that countries with _Common Law_ —as opposed to those with _French civil code_ tradition— tend to protect private property owners, have comparatively more efficient contract enforcement mechanisms and, hence, achieve higher levels of financial development. Mayer and Sussman (2001) find evidence that regulations concerning information disclosure, accounting standards, permissible practice of banks and deposit insurance have significant effects on financial development. Shallow stock markets usually exhibit low levels of shareholder rights (Levine, 1998, 2002; Claessens et al. 2002). Rajan and Zingales (2003) indicate that the joint opening of trade and capital accounts would promote financial development. They argue that elite groups with access to power in countries with trade and financial autarky have strong incentives to resist the development of a more transparent and competitive financial sector in order to prevent new entrants in their markets. In this context, interest groups would support the opening of trade and financial accounts if only they could take advantage of deeper local financial markets and draw resources from a more ample pool of funds, and generate new rents to counterbalance their loss of access to power.

The main goal of this paper is twofold. First, we test whether the increasing crossborder asset trade has led to improvements in the development of domestic financial markets —captured by increasing the size and depth of deposit money banks and other financial institutions as well as deepening stock and bond markets. Second, we examine whether this impact depends upon country-specific characteristics such as the degree of institutional quality, investor protection and trade openness. We collect annual information on financial market development, financial openness and other control variables such as GDP per capita, inflation, trade openness among others for a sample of 145 countries (of which 24 are industrial countries) from 1974 to 2007. We use the identification strategy developed by Faria et al. (2007) and Faria and Mauro (2009) to control for the likely endogeneity of financial openness in our financial development regressions.

Understanding the effects of higher cross-border asset trade on the development of financial intermediaries stock markets and bond markets is crucial due to the impact of financial market development on growth (Levine et al. 2000; Levine, 2005) and, especially, on the direction of capital flows and the persistence of global imbalances (Chinn and Ito, 2007; Gruber and Kamin, 2008). In a seminal paper, Rajan and Zingales (1998) find that _ex ante_ financial market development may help boost the _ex post_ growth of “external-financially-dependent” 4
TABLE 66 sene (Chukm & i ation Imhst#w)_ IV 9mate of Auguimted Cobb-Dougla Prodtion **Fuons -D-endent** Varable - Log of **Co(ant Price** Value Added (Values in paentheses ar sadard earrs)

||Base<br>in|d on Value-A<br>Domestic Pnc|dded<br>e|Based<br>in W|on Value-Ad<br>orld Prices|ded|
|---|---|---|---|---|---|---|
||1|2|3|4|5|6|
|Intercept<br>(% Senegalese Private)|-2.117<br>(2.735)|-3.253*<br>(1.422)|-1.951<br>(1567)|-3.6514<br>(2.083)|-3.799'<br>(1.379)|_2644<br>(1.465)|
|Ownershira:|||||||
|% Senegalese State<br>% French|-0.703<br>(2.239)<br>1356'<br>(0568)|-0564<br>(1.369)<br>0.992<br>(0370)|-1.039<br>(1.280)<br>0.951'<br>(0371)|-2.353<br>(1.657)<br>0.134<br>(0.403)|-1.079<br>(1.067)<br>01i39<br>(0296)|-0.813<br>(0.947)<br>0.427<br>(OM)|
|% Syro-Lebanese<br>% Other Foreig|0.625<br>(0493)<br>2259<br>(0.702)|0.461<br>(0367)<br>1.402<br>(OA52)|0.266<br>(0347)<br>1319<br>(0.438)|0384<br>(0384)<br>0.929<br>(0.649)|0.426<br>(0.345)<br>0.816'<br>(0.422)|0243<br>(0.291)<br>0633'<br>(0354)|
|Trade Variables:<br>Effective Rate of<br>Protection|0.052'<br>(0.029)|0.032e<br>(0.019)|0.021<br>(0.022)|0328'<br>(0.065)|0.341'<br>(0.054)|403S8'<br>(0.049)|
Page 84 10. Having evaluated avallable data sources to ascertain their biases and weaknesses from a gender perspective, and if quantltative gender-disaggregated data is not available, the next scep is to seek alternative information that may provide at least a qualitative indication of the nature and extent of women's activities. Thi3 information may be found in provincial or regional surveys and studies, other case study data, or such alternative sources as observation, interview, or sample survey.

11. For reasons of international conventio-n and data comparabillty, Bank economists may choose not to adjust labor force participation figures to reflect some categories of women's work. But the emphasis here is rather that it remains vital to analytical accuracy that the tasks undertaken by women and the hours spent executing them be properly understood; only then can the opportunity cost of women's labor in different activlties be evaluated.
workplace receive double the wage of those employed in irregular workplaces. Part-time workers of course earn a lot less than full-time workers, and the young (ages 15 – 24) a lot less than older workers. Women earn 12 percent less than men, and are 22 percent more likely to be informally employed. Those without any formal education are more than three times as likely to be informally employed than those Turkish who at least completed high school, and on average earn 52 percent less. Those with some formal education, but no high school completion, are 1.4 times more likely to be informally employed, and earn 39 percent less.

Table 3 presents the 2011 (pre-refugee) distribution of private sector, paid employees across industries, for both women and men (Columns 1 and 3 each sum to 100). For each industry it also reports the fraction employed informally, again separately for men and women. Notably, the table shows that on the whole women are both more likely to be employed in industries with high informality and more likely to be informally employed in a given industry than men. Agriculture is an important source of employment for both genders (around 18 percent of private sector, paid employment). Informality is very high in agriculture, 68 percent for men and a quite astonishing 96 percent for women. Manufacturing industries with high rates of informality (specifically, textiles, clothes, leather, food and wood) employ a 15 percent of men and 22 percent of women, and informality is high among men (27 percent) and even more so for women (48 percent). An exception is construction, which is practically entirely male dominated and has a 54 percent informality rate for men. Wholesale and retail is a roughly equally important source of employment for both genders and the informality rate is about the same. Education and especially household work are female dominated occupations, and the informality rate in household work is 93 percent.

# **2.4 Characteristics of Syrian Refugees**

The Turkish LFS does not, by design, survey refugees. Moreover, currently there is a lack of large-scale, representative surveys of refugees across Turkey and any administrative data that might exist is not publicly available. Fortunately, our empirical strategy does not rely on the availability of refugee characteristics. Important for the interpretation of our findings, however, is the labor force participation rate of Syrian refugees in Turkey. Based on informal discussions with U.S. State Department employees working with refugees in Turkey, it seems that the labor force participation rate of Syrian refugees (of working-age) is very substantial, 11
||**2020**|**2021**|**2022**|**2023**|**2024**|**2025**|**2026**|**2027**|**2028**|**2029**|**2030**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**Bankin**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**g-**<br>**Financi**<br>**ng**||||||||||||
|**Real**<br>**Estate**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Public**<br>**Admin**<br>**istrati**<br>**on**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Educat**<br>**ion**|0.00|0.00|0.02|0.04|0.06|0.06|0.06|0.06|0.06|0.07|0.07|
|**Health**|0.00|0.00|0.02|0.05|0.07|0.07|0.07|0.07|0.07|0.07|0.08|
|**Other**<br>**Servic**<br>**es**|0.00|0.01|0.07|0.14|0.22|0.22|0.22|0.22|0.23|0.23|0.23|

_Table B. 3. Annual spending associated with investments and households’ consumption under the ISUI2 Measure relative to the Reference Scenario by sector of economic activity for the period 2020-2030 (in million euros)_

||**2020**|**2021**|**2022**|**2023**|**2024**|**2025**|**2026**|**2027**|**2028**|**2029**|**2030**|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**Agricu**<br>**lture**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Forest**<br>**ry**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Minin**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**g**||||||||||||
|**Food**<br>**Manuf**<br>**acturi**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**ng**||||||||||||
|**Textile**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Wood**<br>**and**|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|
|**Paper**||||||||||||
|**Chemi**<br>**cal**<br>**and**|0.00|3.50|3.50|1.40|1.40|1.40|1.40|1.40|0.00|0.00|0.00|
|**Plastic**<br>**Produ**||||||||||||
|**cts**||||||||||||
|**Metal**<br>**Produ**|0.00|1.75|1.75|0.70|0.70|0.70|0.70|0.70|0.00|0.00|0.00|
|**cts**||||||||||||
|**Machi**<br>**nery**<br>**and**|0.00|1.75|1.75|0.70|0.70|0.70|0.70|0.70|0.00|0.00|0.00|
|**Equip**||||||||||||
|**ment**||||||||||||
|**Energy**|0.00|-0.10|-0.24|-0.50|-1.22|-1.76|-2.14|-2.89|-2.92|-2.96|-2.98|

36
**Table 3: Estimates of the Effects of Minimum Wages on Hours Worked**

|VARIABLES|Covered –<br>All<br>Log-hours|Covered -<br>Males<br>Log-hours|Covered -<br>Females<br>Log-hours|Uncovered -<br>All<br>Log-hours|Uncovered -<br>Males<br>Log-hours|Uncovered -<br>Females<br>Log-hours|
|---|---|---|---|---|---|---|
|Log-MW|-0.0429|0.232***|-0.181***|0.419***|0.414***|-0.0631|
||-0.0376|-0.0389|-0.0575|-0.0953|-0.0989|-0.343|
|Constant|3.647***|2.232***|5.138***|0.454|1.049**|1.648|
||-0.165|-0.167|-0.334|-0.453|-0.466|-1.972|
|Observations|67,548|41,345|26,203|17,719|13,436|4,283|
|R-squared|0.333|0.157|0.358|0.16|0.077|0.191|

_Notes:_

1. *** p<0.01, ** p<0.05, * p<0.1

2. Data in all regressions are weighted using sample weights.

3. Explanatory variables in the regressions also include: years of education, age, age squared, age cubed, gender, dummies for remuneration order categories, dummies for years, and value added by broad industry.

4. The covered sector is wage-earning workers in the private sector. The uncovered sector are employers and ownaccount workers in the RO sectors wage-earning employees are covered in, as well as the unemployed who have worked before in those sectors.

5. Reported significance levels are based on robust standard errors.

In the uncovered sector, a significant overall effect is found for the sector with a 10 percent increase in the minimum wage being associated with an increase in average number of hours worked of 4.2 percent. The effect is driven by an increase in average work hours among male workers in the uncovered sector.

As we have noted, we test for endogeneity in our OLS regressions and obtain two-stage least squares estimates making use of lagged minimum wages as an instrument for minimum wages as well. The results of the second stage regressions are shown in Table 4 below.

16
# Table 1: List of Variables and Sources

|Variable|Availability|Description|Source|
|---|---|---|---|
|Log of average trade flow|1984-99|Average of real imports and exports between trade<br>partners|Rose (2004)|
|Different Legal Origin|-|Indicator for different legal origins|Djankov et al. (2003) and<br>CIA Factbook|
|Bureaucratic Quality|1984-99|Sum of bureaucratic quality indicators per country pair|International Country Risk<br>Guide (ICRG)|
|Control of Corruption|1984-99|Sum of control of corruption indicators per country pair|International Country Risk<br>Guide (ICRG)|
|Protection of Property Rights|1995-99|Sum of property rights protection indicators per country<br>pair|The Heritage Foundation|
|log distance|-|Great circle distance between trade pair|Rose (2004)|
|log product of GDP|1984-99|log of product of trade pair real GDPs|Rose (2004)|
|log product of land area|-|log product of trade pair land area|Rose (2004)|
|no. of landlocked|-|Number of landlocked countries in trade pair (0, 1, 2)|Rose (2004)|
|no. of islands|-|Number of island countries in trade pair (0, 1, 2)|Rose (2004)|
|common border|-|Indicator for a common border for trade pair|Rose (2004)|
|common language|-|Indicator for a common official language for trade pair|Rose (2004)|
|currency union|1984-99|Indicator for both countries in trade pair members in a<br>currency union|Rose (2004)|
|common colonizer|-|Indicator for common colonizer of both countries in trade<br>pair|Rose (2004)|
|colony-colonizer|-|Indicator for colony-colonizer relationship in trade pair|Rose (2004)|

34