The threat of political extraction and corporate cash holdings: The case of the GCC countries

Figures & data

Table 1. Summary of variable definitions

Variable	Proxy	Sign
Firm size (SIZE)	The natural logarithm of total assets (total assets are measured in US dollars).	+/–
Cash Substitutes (SUB)	Current assets minus cash divided by total assets.	–
Debt Ratio (LEV)	The total of long and short–term borrowings divided by total assets.	–
Capital Expenditures (CAPEX)	Capital expenditures divided by total assets at the beginning of the period.	+/–
Dividends (DIV)	Dividends in dollar value divided by total assets.	+/–
Growth Opportunities (GROWTH)	The market to book value ratio (MTB) is calculated as the market value of equity plus the book value of assets minus the book value of equity divided by assets.	+
Cash flows (FLOW)	Earnings before interest, taxes, and deprecation divided by total assets.	+
Cash Flows Volatility (VOL)	The standard deviation of cash flows (earnings before interest, taxes, and depreciation) over a lagged four-year period.	+
Threat of Political Extraction (CORRUPT)	This variable is measured by the World Bank’s Control of Corruption index which captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests. The definition is obtained from the World Bank.	+/–
Investor Protection (LAW)	This variable is measured by the World Bank’s Rule of Law index which captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. The definition is obtained from the World Bank.	–
GDP Growth (GDP)	Growth in GDP.	+/–
Private Credit to GDP (CREDIT)	The ratio of total private credit divided by GDP.	–

Table 1 summarizes variable operational definitions and their expected sign based on the discussion presented in Section 3.1.

Table 2. Summary statistics by country

	Bahrain	Kuwait	Oman	Qatar	Saudi Arabia	United Arab Emirates
Observations (Number)	86	419	398	126	406	262
Companies (Number)	14	70	77	20	74	40
Average Assets (USD thousands)	351,833	875,136	181,265	3,611,755	4,283,835	3,275,866
Average Cash (USD thousands)	61,868	91,549	17,745	617,997	609,129	377,586
Macro and Institutional Indicators (Averages)
CORRUPT	0.184	–0.073	0.251	1.019	0.028	1.115
LAW	0.397	0.302	0.480	0.832	0.135	0.593
GDP	3.698	1.512	4.127	6.645	3.850	3.553
CREDIT	69.345	74.074	51.419	55.563	44.887	70.813
CASH
Mean	21.92%	15.70%	9.93%	14.48%	10.11%	11.27%
Median	20.83%	10.30%	5.71%	12.18%	6.00%	8.14%
SD	0.138	0.168	0.112	0.104	0.104	0.103
Min	0.004	0.001	0.000	0.003	0.001	0.002
Max	0.578	0.874	0.611	0.492	0.665	0.531

Table 2 reports summary statistics by country. Variables are defined in Table 1.

Table 3. Summary statistics of firm characteristics

	Mean	Median	SD	Min	Max
CASH	0.126	0.083	0.130	0.000	0.874
SIZE	12.619	12.638	1.907	5.996	18.321
SUB	0.277	0.220	0.205	0.002	0.919
LEV	0.213	0.177	0.188	0.000	0.887
CAPEX	0.040	0.026	0.055	0.000	0.755
DIV	0.058	0.034	0.079	0.000	1.051
GROWTH	1.383	1.176	0.796	0.290	8.338
FLOW	0.069	0.068	0.092	–0.625	0.761
VOL	0.039	0.024	0.044	0.001	0.435

Table 3 reports firm-level descriptive statistics for a sample of non-financial firms operating in the GCC countries. Variables are defined in Table 1.

Table 4. Correlation matrix between measures of firm characteristics

	CASH	SIZE	SUB	LEV	CAPEX	DIV	GROWTH	FLOW
SIZE	–0.129 (0.000)
SUB	–0.256 (0.000)	–0.215 (0.000)
LEV	–0.399 (0.000)	0.333 (0.000)	0.065 (0.007)
CAPEX	0.262 (0.000)	0.026 (0.284)	–0.104 (0.000)	–0.331 (0.000)
DIV	–0.095 (0.000)	0.059 (0.015)	–0.098 (0.000)	0.076 (0.002)	–0.008 (0.742)
GROWTH	0.163 (0.000)	–0.017 (0.486)	0.013 (0.585)	–0.170 (0.000)	0.517 (0.000)	0.137 (0.000)
FLOW	0.177 (0.000)	0.113 (0.000)	–0.066 (0.007)	–0.229 (0.000)	0.582 (0.000)	0.109 (0.000)	0.406 (0.000)
VOL	0.091 (0.000)	–0.257 (0.000)	–0.016 (0.523)	–0.081 (0.001)	–0.028 (0.242)	–0.052 (0.034)	–0.031 (0.198)	–0.253 (0.000)

Table 4 reports the correlation between firm-level variables for a sample of non-financial firms operating in the GCC countries. Variables are defined in Table 1. p-values are in parentheses.

Table 5. Estimation results of the cash model—Firm-specific determinates

	OLS	Fixed Effects	Random Effects	GMM
SIZE	–0.007 (–1.40)	0.002 (0.26)	–0.005 (–1.23)	0.002 (0.19)
SUB	–0.125*** (–3.56)	–0.349*** (–5.08)	–0.258*** (–5.53)	–0.432*** (–3.75)
LEV	–0.132*** (–4.33)	–0.096*** (–3.54)	–0.104*** (–4.80)	–0.050 (–1.15)
DIV	0.219* (1.96)	0.201** (2.30)	0.203** (2.37)	–0.009 (–0.08)
CAPEX	–0.209*** (–3.38)	–0.132*** (–2.77)	–0.134*** (–2.86)	–0.261*** (–6.45)
GROWTH	0.018** (1.99)	–0.002 (–0.26)	0.002 (0.27)	–0.007 (–0.66)
FLOW	0.114** (2.18)	0.133*** (2.71)	0.128*** (2.85)	0.077 (1.55)
VOL	0.133 (1.23)	0.209** (2.22)	0.207** (2.21)	0.116 (1.19)
CASHt-1	–	–	–	0.479***
				(5.89)
Time Effects	Yes	Yes	Yes	Yes
Industry Effects	Yes	–	Yes	–
Country Effects	Yes	–	Yes	–
Observations	1697	1697	1697	1118
Groups	295	295	295	246
R^2	0.457	0.152	0.41	–
F Test	16.57***
Hausman Test	54.55***
Arellano-Bond test for AR(2)	–0.741

Table 5 reports the estimation results of the cash model using four alternative estimation methods for a sample of non-financial firms operating in the GCC countries. Variables are defined in Table 1. t-statistics (alternatively z-statistics) are in parentheses. ***, **, * indicate significance at the 1%, 5%, and 10% respectively.

Table 6. Estimation results of the cash model with corruption

	OLS			GMM
	Cash			Cash			Net Cash
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7
CORRUPT	0.036** (2.46)	0.042** (2.47)	0.026* (1.72)	0.055** (2.15)	0.058** (2.32)	0.042** (2.20)	0.106** (2.00)
LAW	–	0.035 (1.08)	0.054* (1.75)	–	0.003 (0.15)	0.010 (0.45)	0.099 (1.09)
GDP	–	–0.001 (–0.68)	–0.001 (–0.80)	–	0.0003 (0.34)	0.0007 (0.09)	0.001 (0.52)
CREDIT	–	0.001 (1.23)	0.002*** (3.10)	–	0.0003 (0.65)	0.001 (1.13)	–0.001 (–0.65)
SIZE	–	–	–0.005 (–1.13)	–	–	0.002 (0.15)	–0.157** (–2.42)
SUB	–	–	–0.130*** (–3.69)	–	–	–0.428*** (–3.74)	–1.130*** (–2.74)
LEV	–	–	–0.141*** (–4.71)	–	–	–0.047 (–1.06)	0.029 (0.28)
DIV	–	–	0.209* (1.88)	–	–	–0.007 (0.06)	0.462 (1.05)
CAPEX	–	–	–0.215*** (–3.39)	–	–	–0.265*** (–6.39)	–0.347*** (–3.71)
GROWTH	–	–	0.017* (1.87)	–	–	–0.007 (–0.68)	–0.023 (–0.89)
FLOW	–	–	0.110** (2.09)	–	–	0.074 (1.49)	0.126 (0.98)
VOL	–	–	0.157 (1.48)	–	–	0.115 (1.17)	0.375* (1.71)
CASHt-1	–	–	–	0.555*** (6.40)	0.553*** (6.49)	0.499*** (6.15)	0.424*** (6.99)
Time Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry Effects	Yes	Yes	Yes	–	–	–	–
Country Effects	Yes	Yes	Yes	–	–	–	–
Observations	1697	1697	1697	1118	1118	1118	1118
Groups	295	295	295	246	246	246	246
R^2	0.3138	0.3152	0.4538	–	–	–	–
Arellano-Bond test for AR(2)	–	–	–	0.198	0.209	–.738	–1.026

Table 6 reports the estimation results of the cash model with corruption using OLS robust standard errors clustered by firm in the first three models and GMM robust standard errors in the fourth and fifth columns. The estimation uses net total assets (assets minus cash) to compute a variation of the CASH and SIZE variables in the specification reported in column 5. Variables are defined in Table 1. t-statistics (alternatively z-statistics) are in parentheses. ***, **, * indicate significance at the 1%, 5%, and 10% respectively.

Table A1. Cash model for individual GCC countries

	Bahrain	Kuwait	Oman	Qatar	Saudi Arabia	United Arab Emirates
SIZE	0.058 (1.40)	–0.002 (–0.12)	–0.020** (–2.00)	0.033*** (8.73)	0.020 (1.61)	0.013 (0.80)
SUB	–0.677*** (–4.81)	–0.224** (–2.10)	–0.207*** (–3.60)	–0.210** (–2.59)	–0.387*** (–3.27)	–0.243* (–1.89)
LEV	–0.008 (–0.02)	–0.057 (–1.06)	–0.103*** (–3.21)	–0.106* (–1.74)	–0.196*** (–3.07)	–0.157* (–1.91)
DIV	–0.164 (–0.11)	0.406*** (3.13)	–0.041 (–0.23)	–0.654** (–2.51)	0.080 (0.49)	0.140 (1.09)
CAPEX	–0.301 (–1.22)	–0.184*** (–3.09)	–0.146*** (–3.16)	0.124 (0.88)	–0.063 (–0.62)	–0.252*** (–3.09)
GROWTH	–0.017 (–0.22)	0.005 (0.37)	0.021 (1.28)	0.022 (1.02)	–0.015 (–1.26)	–0.004 (–0.22)
FLOW	–0.005 (–0.02)	0.153** (2.15)	0.180** (2.57)	0.812*** (3.59)	0.159 (1.30)	0.052 (0.70)
VOL	–0.386 (–0.72)	0.207 (1.39)	0.225 (1.60)	–0.547 (–0.85)	0.475** (2.28)	0.129 (0.76)
Observations	86	419	398	126	406	262
Groups	14	70	77	20	74	40
R^2 (Overall)	0.873	0.583	0.552	0.749	0.323	0.50

This table reports the estimation results of the cash model for individual GCC countries using the random effects model. The estimation includes year and industry effects. Variables are defined in Table 1. z-statistics are in parentheses. ***, **, * indicate significance at the 1%, 5%, and 10% respectively.