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Firms in MENA Economies: Stylized Facts
In this section, following the performances of 76 cohorts of firms that entered the market between 1934 amd 2009 in four MENA economies (Egypt, Lebanon, Mo-rocco and Tunisia) during the fiscal year of 2012, I present some of the important stylized facts on job creation, firms’ dynamics and investment behavior as well as discouragement and access to finance.
Figure 1.9-(a) indicates the employment growth across different cohorts of firms. It captures the unconditional 22 inverse exponential relation between age and em-ployment growth.
Bank’s supply for external finance
First, I look at supply side where banks are lenders with inelastic supply. They finance their required funds at the risk free interest rate r in a deposit market. Fur-thermore they face pool of applicants, including firms that are heterogeneous in terms of the risk and return of of the their investment projects. θi denotes the risk for firm i. It indicates that with probability of θi the investment project of borrowers going to succeed and with probability 1 − θ its investment will fail. Bank could not distinguish among different types of applicants therefore it makes its decision on the risk of investment plan and terms of the contract based on its realized average risk from pool of applicants in the last period. B ¯ + (1 ¯ (1.2) Πt+1 = [θt Rt+1 − θt )(1 + r)ζ(1 − η) − (1 + r)] ζ (1 − η) ǫ [0, 1] is the « Effective collateral rate » adjusted by interest rate. Follow-ing Barro (1976) Chan and Kanatas (1985) and Jappelli et al. (2005) , we assume there is a disparity between collateral valuation by the borrowers and the bank. This dis-parity are related to the transactions costs, the bank faces in taking possession of and liquidate the collaterals in an event of default. We denote this transaction cost by ηǫ[0, 1]. The transactions costs reflects institutional quality 23. In my context they indicate the quality of collateral and bankruptcy laws in each country.
Considering banks as competitive risk neutral lenders, the rationing interest rate R in credit market is determined by setting the expected profit equal to zero. Hence For given rate of collateral requirement, the inelastic supply of credit will be defined 23Coase (1960) and North (1992) by interest rate R as following Rt+1 = (1 + r) [1 − ζ(1 − η)(1 ¯ (1.3) ¯ − θt )] θt It worth to note that, the higher expected average risk of applicants increases the interest rate spreed. However higher collateral rate covers part of this risk that bank faces and thus it reduces the cost of bank’s finance. Nonetheless, the higher trans-action cost η , diminishes the effectiveness of collateral. Thus the lower expected recovery rate 1 − η , increase the interest rate spreed and tightens the credit supply which in line with empirical evidences such as (Djankov et al. (2007) and BAE and Goyal (2009))
Firms’ demand for external finance
In my framework,economy populated by risk neutral firms that decide to carry out a fixed investment through external finance by considering the return and risk to their investment project as well as the cost of external credit. With probability of θ their investment project will be successful and it returns A for each unit of capital. Successful firms then return rate R to the banks in second period. With probability of 1 − θ , their investment fails with zero return . Hence they default on their loan and the bank seizes their collaterals . Therefor Firm i expected return from investing one unit of external credit could be written as following: period. ΠiF t+1 = θi (Ai − Rt+1) − (1 − θi )(1 + r)ζ.
Firm i which carrying out the project with return Ai with probability of θi decides to apply for a bank loan if ΠiF t+1 ≥ 0 Therefore we could write down the elastic demand which denotes the participation condition for firm i as following Ai θi Rt+1 + (1 − θi )(1 + r)ζ θi.
The collateral rate has two effects on demand of firm i. First, the direct effect that discourages firm to apply for external fund as it reallocate some of the risk involved in the investment from the bank toward the firm. Then there is a indirect effect through the interest rate R. The higher collateral rate reduce the interest rate spread which increase firm’s incentive to apply. By replacing R from first stage we could see the outcome of these two opposite effects. Ai (1 + r)[ 1 − ζ( 1 − 1 )+ηζ 1 ] (1.4) ¯ ¯ ¯ θt θ θi θt.
Effectiveness of Collateral and Quality of institutions
The four propositions that have been outlined in previous subsection suggest that in presence of transaction costs, the aggressive collateralization could raise alloca-tional inefficiency against entrepreneurial firms (high risk borrowers) by discourag-ing them to apply for a loan .In developing country with lower institutional quality , higher judicial inefficiency and limited law enforcement , banks face more barriers to liquidate the collaterals and thus collateral lending is subject to higher transaction cost . This implies that miscalculation against young firms through discouragement is more likely and more severe in developing countries .Figure 1.11-(a) visualize this comparison between developed and developing countries.
The MENA Enterprise Survey
Our data comes from The Middle East and North Africa Enterprise Survey (MENA ES), funded jointly by EBRD, EIB and the World Bank. The MENA ES provides the firm level data of the formal private sectors in our sample of four MENA economies: Egypt, Lebanon, Morocco and Tunisia . The survey covers manufacturing and ser-vice firms with at least five employees, where services includes retail, wholesale, hospitality, repairs, construction, transport and information technology (IT) sectors. However sectors such as agriculture, fishing, and extractive industries, as well as utilities has been not covered in the survey. Also some of services sectors such as financial services, education, and healthcare has been not included in the survey. The MENA ES addresses a broad range of business environment issues such as access to finance, The organization and quality of firms, managers characteristics , market structure and the political instability that firm faces, as well as their per-formance measures. The samples are stratified by firm size, sector of activity, and location within these four economies. The survey covers 6083 firms in total with sample size ranging from 407 firms in Morocco to 2897 in Egypt. The MENA ES follows the World Bank’s global methodology for enterprise surveys. The data are therefore comparable with enterprise surveys in 126 countries covering more than 94,000 firms. EBRD et al. (2016) presents first results of the MENA ES. Data collec-tion took place in the aftermath of the Arab Spring. Respondents were interviewed in 2013 and 2014, but the reference period of the survey is firms’ fiscal year 2012.
Firm’s Performances and Characteristics
Firms’ performance in terms of job creation is our variable of interest that we seek to explain. We compute employment growth through expansion for all incumbent firms comparing the number of their full time employees at the end of last fiscal year and three fiscal years ago. tLFY − tFY−3 αlLFY + (1 − α)lFY−3 gi = 1 lLFY − lFY−3 (1.13).
A common choice of weight is to set α = 1/2. It has the advantage of making the growth measure symmetric and more comparable across different size groups(Moscarini and Postel-Vinay (2012)). By design the survey only covers firms that have survived until the interview. Therefore I could not observe job creation and destruction by entry and exit of firms. This narrows down my analysis to intensive margin of firms’ ability to create jobs. Furthermore this also implies that my results are sub-ject to survivor bias in the sense that I cannot observe firms that have exited since FY−3. Moreover as I try to explain the pattern of employment growth through access to external finance , I investigate the firm’s performance in terms of fixed investment. MENA ES provides information on whether firms have purchased fixed asset dur-ing the last fiscal year. I construct a set of control variables that may plausibly affect the ability of the firm to either grow or carry out fixed investment. In particular, the MENA ES questionnaire includes three questions which pro-vide information on characteristics and quality of firm’s manager: gender, educa-tion and experience . Manager education assume a value of 1 if the manager holds a university degree and 0 otherwise. manager experience captures how many years of experience the manager has in the present sector. Female CEO is a dummy variable that indicates whether the top manager is female. Bloom and Van Reenen (2007) highlights the importance of manager’s characteristics and argues it could attribute to explain the differences that exist in performance of firms even within narrowly defined sectors The MENA ES further provides information on the organization of firms. The variable Foreign ownership is a dummy variable that takes the value of 1 if it at least 10 percent of the firm is owned by foreign private individual or company. Foreign-owned firms may have access to internal capital markets and therefore be less de-pendent on the local banking system. The questionnaire also elicits firms’ age and their initial size three fiscal yeas ago. The firms’ employment growth are highly re-lated to their initial size as the employment growth often slows down as the num-ber of employees increase. Also firm’s ability to grow and their strategic decision to carry out an investment highly depends on the life cycle of firms.
Finally, I construct three measures of firm quality. Audited equals one if the firm’s accounts have been certified by an external auditor. This reduces information asym-metries and thereby facilitates access to finance. Exporter is an indicator equal to one if the firms exports at least ten percent of sales. This signals that the firm is compet-itive in international markets. Finally, Iso Holder indicates if the firm has earned a quality certification recognized by the International Organization for Standardiza-tion (ISO).Summary statistics are provided in Table REF. Some other studies such as Gorodnichenko and Schnitzer (2013) that use similar data (BEEPS) control in ad-dition for total factor productivity, estimated based on cost shares for labour, mate-rial, and capital, adjusted for capacity utilization. Item non-response to quantitative questions in the MENA ES is high implying a large and likely non-random loss of observations, as a result of which I decide to not control for TFP.
Table of contents :
Introduction in French
I.1 Préface
I.2 Environnement collatéral et système bancaire dans les pays du MENA 7
I.3 Qualité des législations de résolution des garanties et des faillites dans les pays du MENA
I.4 La répartition de la création des emplois au cours du cycle de vie et des entreprises et son rôle sur la création d’emplois
I.5 La répartition de l’emploi entre les secteurs et son rôle sur le niveau d’emploi
Introduction in English
II.1 Collateral environment and banking system in MENA countries
II.2 Quality of collateral and bankruptcy law in MENA countries
II.3 Distribution of job creation over firms’ life cycles and why it matters
II.4 Distribution of employment across sectors and why it matters
Collateral Regimes and Discouragement
1.1 Introduction
1.2 Job Creation , Entrepreneurship and Discouragement
1.3 Firms in MENA Economies: Stylized Facts
1.3.1 The Model
1.3.2 Financial Contract
1.3.3 Bank’s supply for external finance
1.3.4 Firms’ demand for external finance
1.3.5 The Risk Return Structure of firms
1.3.6 The allocational effect of collateral
1.3.7 Implication of the model
1.4 Data
1.4.1 The MENA Enterprise Survey
1.4.2 Firm’s Performances and Characteristics
1.4.3 Access to Finance
1.5 Identification strategy: Non experimental treatment design
1.6 Results
1.6.1 Firms’ Performances and Local collateral Policy
1.6.2 Main Findings
1.6.3 Robustness Check: Alternative indexes for age and collateral Environment
1.6.4 Analysis of Subsamples
1.7 Conclusion
Collateral Regimes and Disconnection
2.1 Introduction
2.2 Data
2.2.1 The MENA Enterprise Survey
2.2.2 Access to Finance
2.2.3 Employment growth and control variables
2.3 Measuring credit constraints
2.4 Empirical strategy
2.5 Results
2.5.1 Estimating banks’ collateral policies
2.5.2 Local collateral practice and employment growth
2.5.3 Financial channels
2.5.4 Robustness checks
2.6 Concluding Remarks
Structural Change and the China Syndrome
3.1 Introduction
3.2 Exposure to Imports from China and Structural Change in OECD Countries: Stylized Facts
3.3 A Simple Model
3.3.1 The production side
3.4 The changing nature of Chinese trade and technological change
3.4.1 Technological change and depreciation of capital
3.5 Data and Empirical Strategy
3.5.1 Data
3.5.2 Index of Exposure to Chinese Imports
3.5.3 Identification
3.6 Results
3.7 Concluding Remarks
Bibliography
