Advance Dynamic Panel Second-Generation Two-Step System Generalized Method of Movement Modeling: Applications in Economic Stability-Shadow Economy Nexus with a Special Case of Kingdom of Saudi Arabia

Abstract

Applying an advance dynamic panel second-generation two-step system generalized method of movement modeling, this study endeavors to bridge the gap in the literature by examining the association between shadow economy and economic stability in multiple countries with a special case of the Kingdom of Saudi Arabia. The study has been motivated by the evidence that the shadow economy is a persistent source of the decline in tax revenue, which is the main source of funds for any economy to run welfare packages for the public. In addition, it also impacts the economy’s financial stability and amplifies the losses. Saudi Arabia is selected as a special case given its global significance and participation in the group of the fastest growing economies in the world. Thus, this study finds a negative association between the shadow economy and economic stability in the case of the full sample and a sub sample of Saudi Arabia. In other words, our study supports the point of view of those scholars who claim that the shadow economy is harmful to the economy. Based on the empirical findings, the study recommends that policymakers need to give importance to the shadow economy while formulating economic stability policies in the case of a full sample, especially in Saudi Arabia. Similarly, the robustness of the results is tested using different model specifications and alternative estimation techniques.

1. Introduction

After the 2008 financial crisis, the economic situation of many economies became volatile. Many factors were responsible for such economic instability in these countries, such as high debt, slow economic reforms, low quality of institutions, and crimes. On the other hand, weak labor market conditions and future uncertainty about the equity markets created a deficiency in consumer and investor confidence. In this vein, an important determinant of instability is the shadow economy, as studies report that economic crises pushed many people into the informal economy [1]. Previous decades witnessed a paucity of empirical research on the shadow economy. Thus, understanding the shadow economy’s determinants can shape discourse and practice. The shadow economy provides firms and individuals with a place to escape their financial activities from financial regulators.

The shadow economy consists of all unregistered economic activities that become official production if counted [2,3]. There are many drivers of the shadow economy. Therefore, it is important to curtail the factors which cause the shadow economy and to bring back businesses and laborers into the mainstream economy. On the other hand, one of the main objectives of the economic policy of any government is the stability of an economy. Governments attempt sustainable economic growth to minimize possible unemployment levels, stabilize prices, and stabilize the exchange rate [4]. Economic policies, such as tax policies, government spending, rule and regulations, and fiscal and monetary policies, are crucial in achieving these objectives. So, economic stability has theoretical importance and a vital role in terms of its real and practical importance. The famous economist [5] introduced government intervention in the economic life of society and established macroeconomics, while [6] incorporated economic growth into Keynesian theory.

Similarly, [7] and [8] concluded that growing economies tend to have a stable long-run equilibrium with time. To reflect the real picture of economic phenomena, [9] stressed the medium approach where there is both the short-run (involuntary unemployment and business cycles) and the long-run (e.g., economic growth). Because from the practical point of view, the economies are neither too uneven nor too stable and are conditional on continuous cyclical fluctuations, i.e., the recession and depression stage.

The shadow economy is a menace to every economy, impacts tax collections, and leads governments to depend on borrowings. These borrowings bring more burden and may result in financial instability [10]. This indirect impact of the shadow economy on financial stability is not given justified importance and needs to be explored in detail. The lack of empirical research on the consequences of the shadow economy on financial stability motivates this study. This study intends to provide insights into the complex relationship between financial stability and the shadow economy. To fill this gap, this study measures the impact of the shadow economy on financial stability.

The current condition of the world economy is still weakened compared to the last year and creates new challenges for policymakers. The UK economy has moved to a new macroeconomic framework to continue to a more stable economic condition [11,12]. According to the UK maintaining economic stability report (2001), the goal of any government is to move to a stable, long term and persistent economic condition. Generally, the main economic aims of government are: (i) persistence of economic stability, (ii) reducing unemployment to the possible level, (iii) controlling inflation, (iv) uprising social and economic well-being, and (v) environmental protection.

Figure 1 and Figure 2 reports that the size of the shadow economy is high between Organization of Islamic Cooperation (OIC) and non-OIC economies.

Here, in Figure 1, we notice that in the case of a sub-sample of non-OIC countries, the size of the shadow economy is approximately 30%, where most countries are again on the fitted line where the fitted line is significant at a 95% level of significance.

Figure 2 relates to the average size of the shadow economy in the case of OIC; we observe that majority of countries are clustered above 35% and are on a fitted line where a major part of the fitted line is above 30%, which shows that the size of the shadow economy in OIC countries remain higher than non-OIC countries. Figure 3 reports that the size of the shadow economy is 15% on average and is in decreasing trend in the case of Saudi Arabia.

A shadow economy can be beneficial to economic growth and stability and vice-versa. Some scholars consider that the shadow economy harms the official economy and delays its development and growth [13]. A shadow economy creates many hurdles for the government, and it reduces the tax revenue because part of the economic activities happening in the country is not taxed and evades taxation, while taxes is one of the main sources of government revenue. Similarly, the shadow economy also reduces the supply of public goods and services and undermines public revenue. Public deficits will rise as the shadow economy undermines government revenue for a given amount of government expenditure. It will pressure the interest rates and lead to increasing inflation [14]. The large size of the shadow economy also leads to a higher tax burden on those operating in the formal economy and creates unrest among the governments and the public.

Similarly, the shadow economy also leads to a possible breakdown in the law-and-order conditions of the country [15]. It is the shadow economy that misallocates the resources [16]. For example, official statistics show that workers participating in the shadow economy are considered unemployed. Similarly, the goods and services produced in the shadow economy are relatively cheaper as there is no taxes and regulations cost. Once these goods are available in the market along with official goods, it hurts the market conditions and distorts the competition in the market [17].

Similarly, the shadow economy also disrupts other economic variables, such as undermining official unemployment statistics, labor force, goods and services produced in the economy, etc. Therefore, economic policies based on erroneous statistics lead to ineffective, counterproductive effects. GDP figures are under the veil due to the shadow economy and cause the macroeconomic variables to be unreliable [17]. The large size of the informal economy causes welfare loss by plummeting public revenue. In the word of Ikiz [18], countries with low-size shadow economies have good economic growth and development compared to low GDP per capita in the case of a large informal economy.

On the contrary, there is the view that the shadow economy positively impacts the economy. Especially this positive aspect view, which originated from Latin American economies, maintains that the shadow economy is a source of economic growth and stability. Similarly, in the UK, total spending increases in the long run [19]. Looking from the perspective of the labor-leisure paradigm, the working hours in the informal economy are flexible, and there are no strict terms and conditions of labor law to be followed [20].

According to [21], a shadow economy is a place of innovation, providing space to create innovative production procedures. At the same time, [22] argues that the shadow economy is the response of the lower and middle classes of people and businesses to government regulations. Similarly, the shadow economy also plays an important role in the official economy by providing goods and services, side by side, with the formal economy [23], where normally the goods and services produced in the informal sector are relatively cheaper, which enables the deprived class of society to benefit from them.

Similarly, the newly participated labor force takes advantage of the shadow economy by using it as a training center. Later, they can use the skills and experience they have learned in the shadow economy. The shadow economy helps the formal economy, especially during economic recession and crisis, where the labor force who lose jobs in the formal economy gets the benefit of the informal economy to switch there and earn their livelihoods [24,25]. Finally, the shadow economy has a fast investment multiplier. It rises aggregate demand and economic welfare because one-third of the income generated in the informal economy is used directly in the official economy [26,27]. The overall objective of this study is to explore the association between the shadow economy and economic stability and bring forth a set of suggestions to curtail the shadow economy in the sample economies, including the Kingdom of Saudi Arabia, as a special case.

The Economy of Saudi Arabia and the Shadow Economy

Of the Group of 20 countries, Saudi Arabia’s economy will continue to expand at the quickest pace owning to broad pro-business policies and a significant increase in oil prices and production drive resurgence [28,29]. Saudi Arabia has a thriving economy attributable to its vast oil reserves. With oil income contributing to over 50% of its GDP and 70% of its exports, it is recognized as one of the major oil exporters in the world (Organization of Petroleum Exporting Countries, 2021). The Saudi economy has progressively attracted international investment since entering the World Trade Organization in 2005 and has garnered interest from a wider public owing to the objectives of Vision 2030. Significantly, the kingdom’s Vision 2030 calls for reshuffling the labor market, strengthening the business ambiance, and advancing the financial and supervisory framework [30]. The motivation for selecting Saudi Arabia for case analysis is based on the fact that the oil-based economy is making the transition toward a diversified economy under the leadership of its Saudi Arabia Vision 2030 plan. Future Saudi economic growth will face several obstacles, including control of the shadow economy. Thus, the shadow economy in Saudi Arabia needs to be explored. Formulating policy measures relevant to Saudi Arabia’s shadow economy requires a country-specific analysis. The growth of the shadow economy substantially impedes a country’s capacity to develop sound institutions. Against this backdrop, this study employs advanced econometric tools to examine the linkage between the shadow economy and economic stability in Saudi Arabia’s economy.

This study contributes to the body of literature in the following dual ways. It is the first systematic effort to explore the association between shadow economy and economic stability in selected 141 countries for the period 2004–2015, adding to the investigation on this theme and helping to promote strategic policymaking to address this issue. Therefore, we contribute to the limited literature on this theme. Moreover, in this study, we endeavor to cover the shadow economy in the case of the Kingdom of Saudi Arabia as a special case as it highlights a crucial gap in the studies.

Second, we employ advanced econometric tools as we employ a two-step differenced Generalized Method of Moments (GMM) and a panel ordinary least square (POLS) fixed effect model (FE) and random effect (RE) to investigate the purported relationship. The results are robust from a methodological standpoint. Based on the findings of the empirical analysis, we report that the shadow economy is negatively associated with economic stability. In other words, the size of the shadow economy matters in destabilizing the official economy.

Furthermore, our study will be valuable to policymakers and key stakeholders. We find that the shadow economy is a significant predictor of economic stability, which is desirable to all economies for smooth functioning and growth. The shadow economy amplifies the economy by reducing financial stability and lowering tax revenues. The following is the order of our paper. Section 2 briefly describes the literature, and Section 3 of the study explains the methodology. Section 4 discusses the results, and Section 5 covers the conclusion and policy implications.

2. Literature Review

This paper pertains to two distinct works of literature. The first strand focuses on the recent studies covering the current perspective on the shadow economy. The studies of [31] and [32] demonstrate that the shadow economy enhances pollution and energy usage; both are deleterious to environmental sustainability. They [2] add to the body of knowledge and empirical evidence that may be significant to theory and practice by establishing that the shadow economy diminishes to its minimal magnitude when the financial sectors are fully matured. They [33] suggest that trade liberalization is a major component in containing the shadow economy, emphasizing export diversification and international quality. He [34] reveals that as economic complexity advances, the relative size of the shadow economy (as a percentage of official GDP) reduces; over time, economic complexity has shown to have a detrimental effect on both the relative and absolute dimensions of the shadow economy.

He [35] reveals that e-government is a powerful method for decreasing unlawful business activity. E-government has a significantly greater long-term impact on reducing informal output than it does shortly. They [36] examine how the scale of the shadow economy and access to financial services affect developing countries’ economic growth between 2008 and 2017. The research shows that the shadow economy negatively impacts economic growth in developing economies. In contrast, access to finance has a statistically significant positive impact on economic growth. They [37] investigate whether the shadow economy is procyclical or countercyclical over the business cycle using a panel of 123 studied countries between 1991 to 2017. The findings show that the shadow economy demonstrates countercyclical performance throughout the business cycle, which is cited in non-OECD economies.

Additionally, it reveals that the response to economic cycle expansions and contractions is proportional in the long haul, with the shadow economy reacting more substantially to booms than declines in the near term. They [38] explore the connection between economic development, the shadow economy, and 18 specified economies in transition between 2002 and 2015. The GMM analysis show that economic growth indicators have a statistically significant and adverse effect on shadow economy magnitude. The findings also show a positive correlation between inflation, public spending, shadow economy size, and an inverse relationship between the shadow economy and the stability of the rule of law in emerging economies. The study also reports that by strengthening the rule of law and economy, shadow economy size in transition economies can be minimized. They [39] highlight that the shadow economy is a multifaced phenomenon across both emerging and developed economies.

The second strand discusses the main drivers of the shadow economy. The presence of the shadow economy around the world has stimulated the interest of researchers and policymakers to know the main causal factors behind its progress and growth [40,41]. GDP is the market value of all registered goods and services produced in the economy. Similarly, the shadow economy also contains the market value of all the unregistered goods and services produced in the country. According to [42] shadow economy consists of those goods that are even legal but are purposely hidden from the government authorities to escape and evade income tax, labor market regulations, safety standards, value-added tax, social security contributions, and administrative measures. The following are the main drivers of the shadow economy.

2.1. Taxation

The tax burden is one of the key drivers of the shadow economy as it influences the worker’s labor and leisure time distribution and increases the cost of doing business [43,44,45]. After disturbing the labor and leisure setting of workers, they would look for other options (shadow economy) to maintain the previous labor-leisure distribution. This switching to the shadow economy will decrease, on the one hand, the government revenues and, on the other hand, will increase social and public expenditure as these people are now considered unemployed in the government documents. Still, they are employed directly in the shadow economy. So, the gap between government taxes and government expenditure will increase, and the government will compel to run a deficit budget. This scenario has been captured in the following Figure 4. As revealed in the following diagram, part of the money (tax evasion) will shadow the economy because government revenues decrease while having high spending and thus leading to a budget deficit.

According to [46], even restructuring the tax system cannot decrease the shadow economy. Even in advanced economies, taxes significantly impact the shadow economy [47,48]. Similarly, [49] finds that tax burden and shadow economy have a positive connection. In the case of Pakistan, tax evasion boosts the shadow economy and thus brings inequality and increases poverty [50].

2.2. Regulations

According to the legalist school of thought, over-regulation pushes people into the shadow economy. This school of thought suggests that to address the issue of the shadow economy, there is a need to decrease regulations because the regulations, in the first place, increase it. In other words, the solution to reduce the size of the shadow economy is to make a business-friendly environment in the official economy. It is considered by [22] that a shadow economy is the reaction of a poor class of society to the catastrophe of official authorities to supply goods and services which fulfill their needs and necessities as well as to offer them effective services in terms of easiness in business registrations and labor market policies. The government authority also needs to allocate economic resources to promote equality among citizens; if not, then the gap between both classes, i.e., upper and lower, will increase, and as a result, society will move toward social unrest and unfairness. Under this paradigm, people are joining the shadow economy because it is the best and more utilitarian alternative. According to [51], the presence of a shadow economy is an indication and sign of excessive rules and regulations in the country. In the same way, it demonstrates a clear picture of the country’s economic and social condition.

2.3. Government Expenditure

One of the main objectives of policymakers is to increase economic growth and bring economic welfare. However, people’s choices to operate in a shadow economy are closely linked to formal economic growth [41]. If the official economy is facing downfall and recession, citizens will move to a shadow economy to maintain their current expenses and recompense a decrease in their salaries and revenues. On the other hand, if the official economy is booming and growing, it will attract people from the shadow economy to operate in the official economy to get higher returns and good compensation [42]. If people feel that they are getting appropriate goods and services for the taxes paid to the government, they will operate in the official economy; otherwise, they will work in a shadow economy. Similarly, unproductive government expenditure leads to a boost in the size of the shadow economy because unnecessary and irrational increases in taxes may lead to switching towards the shadow economy. According to the classical school of thought, improper government expenditure crowd out private investment because of distorting the business environment in the market. Similarly, because of misuse of government revenue, government military expenditure increases the size of the shadow economy.

The association between the shadow economy and economic performance is ambiguous. This paper explores the shadow economy’s impact on economic stability. To examine the relationship between the shadow economy and economic stability, this study hypothesizes that the shadow economy is associated with economic stability.

3. Data and Methodology

For this study, we have selected 141 countries, and the financial freedom and investment freedom variables data have been collected from World Heritage Foundation (WHF). Macroeconomic variables data are taken from World Development Indicator (WDI), and governance variables data have been extracted from World Governance Indicator (WGI) for 2004–2015. Considering the main drivers of economic growth and stability, the control variables have been selected based on the literature. Following the literature on economic stability, we have selected two proxy variables for economic stability. We use GDP growth as a proxy for economic stability to check the impact of the shadow economy on economic stability because GDP is arguably a well-established measure of economic stability among academicians and scholars [52]. However, to capture the true picture of economic stability, we have also used the standard deviation of GDP as another proxy for economic stability. Our focal variable is the shadow economy (% of GDP). The data for the shadow economy comes from [53]. They estimated the shadow economy using the Multiple Indicators and Multiple Causes (MIMIC) model. Compared to other models, such as the currency demand approach or electricity consumption technique, etc., this MIMIC model is considered the best method to estimate the size of the shadow economy as it considers both causal and indicator factors of the shadow economy.

Similarly, we also consider control variables that may impact economic stability. These variables cover exchange rate (ER), trade (T), tax burden (TAXB), government expenditure (GE), financial freedom (FF), gross capital formation (GCF), education (EDU), political stability (PS), the rule of law (ROL).

Table A1. List of variables.

Variable	Description	Sources
GDP	Gross Domestic Product (Annual %)	World Development Indicators [12]
SDGDP	Standard Deviation of GDP	Own Calculation
SE	Shadow Economy (% of GDP)	Schneider and Medina [51]
T	Trade (% of GDP)	World Development Indicators [12]
TAXB	Tax (% of GDP)	World Development Indicators [12]
GE	Government Expenditure (% of GDP)	World Development Indicators [12]
FF	Financial freedom (percentile Rank)	The Heritage Foundation
ER	Real effective exchange rate index (2010 = 100)	World Development Indicators [12]
ROL	Rule of Law (Percentile Rank)	World Governance Indicators [12]
GCF	Gross capital formation (annual % growth)	World Governance Indicators [12]
INVF	Investment Freedom (Percentile Rank)	The Heritage Foundation
Edu	School enrollment, secondary (% gross)	World Governance Indicators [12]
PS	Political Stability (Percentile Rank)	World Governance Indicators [12]
U	Unemployment (% of Total Labor Force)	World Development Indicators [12]

provides details of the variables used in this study.

To study the impact of the shadow economy on economic stability, we develop the following model:

$$E{S}_{it}=\alpha +\gamma E{S}_{it-1}+\delta S{E}_{it}+\lambda contro{l}_{it}+{\mu }_i+{\nu }_t+{\epsilon }_{it}$$

(1)

where the $E{S}_{it}$ denotes economic stability, $E{S}_{it-1}$ represents the one-period lag of the dependent variable, i.e., economic stability as a right-hand side variable to control for possible persistency and smoothness over the time, $S{E}_{it}$ signifies shadow economy,$contro{l}_{it}$ includes all control variables, such as education, government expenditure, etc. Likewise, $\mathsf{\gamma },\delta ,\beta and \lambda$ are parameters,${\nu }_t$ refers to period-fixed effect, ${\mu }_i$ states the country-fixed effect, the ${\epsilon }_{it}$ is an error term, and i and t denote country and time, respectively.

Considering the persistent nature of many variables in our data set, the variables have lagged values having less control over predicting their future realizations; as a result, the standard difference-GMM estimator becomes less preferable. Therefore, we are employing the second-generation System GMM system technique, which has many advantages over other panel procedures, such as addressing heterogeneity across countries that could affect the size of the shadow economy and economic stability and make fallacious results. Similarly, it can also handle the general issue of panel technique, i.e., the suitability of instruments. Additionally, it is also appropriate to address the issue of small-time series. Finally, it also relaxes the assumption of homogeneity in the sample. The same methodology is adopted by [2].

To investigate the impact of the shadow economy on economic stability in the case of Saudi Arabia, we develop the following model:

$$E{S}_t={\beta }_0+{\beta }_1 S{E}_t+{\beta }_{2}contro{l}_t+{\epsilon }_t$$

(2)

where the $E{S}_t$ denotes economic stability, $S{E}_t$ signifies shadow economy,$contro{l}_t$ includes all control variables. Likewise, ${\beta }_0$ is intercepts, ${\beta }_1$ and ${\beta }_2$ are slope coefficients, ${\epsilon }_t$ is an error term, and t denotes time, respectively.

4. Results and Discussion

Table 1. Descriptive statistics.

Variable	Obs.	Mean	Std. Dev.	Min	Max
GDP	1678	3.99	4.52	−36.70	38.00
SDGDP	1678	2.53	2.76	0.01	23.33
SE	1679	29.83	12.10	7.96	69.08
T	1677	91.49	56.74	21.12	442.62
TAXB	1670	75.19	12.59	32.00	99.90
GE	1665	15.36	4.95	2.05	31.57
FF	1670	53.28	18.61	10.00	90.00
ER	990	99.37	13.45	53.75	328.25
ROL	1680	49.47	29.27	0.47	100.0
GCF	1656	1.12	4.02	4.69	5.02
INVF	1670	54.24	20.73	0.00	95.00
EDU	1287	81.91	28.93	8.77	163.93
PS	1680	45.73	27.47	0.47	100.0
U	1668	8.094	5.29	0.10	37.60

(GDP) is Gross Domestic Product, and (SE) is the shadow economy. All the other variables include (SDGDP) standard deviation of GDP, (T), (TAXB), (GE), (FF), (ER), (ROL), (GFC), Investment Freedom (INVF), (EDU), (PS) and Unemployment (U). For detailed descriptions, refer to Table A1.

and

Table 2. Correlation analysis.

	GDP	SDGDP	SE	T	TAXB	GE	FF
GDP	1
SDGDP	−0.05	1.00
SE	0.09	0.07	1.00
T	0.04	0.05	−0.25	1.00
TAXB	0.15	0.07	0.18	0.11	1.00
GE	−0.24	−0.05	−0.30	0.04	−0.34	1.00
FF	−0.14	−0.08	−0.40	0.30	−0.12	0.34	1.00
ER	−0.13	0.03	−0.03	0.00	−0.02	−0.01	0.00
ROL	−0.21	−0.11	−0.66	0.30	−0.30	0.51	0.67
GCF	−0.02	−0.08	−0.32	−0.17	−0.15	0.06	0.06
INVF	−0.19	−0.03	−0.43	0.27	−0.20	0.34	0.73
EDUS	−0.31	−0.04	−0.50	0.24	−0.21	0.44	0.49
PS	−0.16	−0.04	−0.54	0.40	−0.24	0.42	0.54
U	−0.11	0.01	0.04	−0.06	−0.03	0.19	0.03
	ER	ROL	GCF	INVF	EDU	PS	U
ER	1.00
ROL	−0.01	1.00
GCF	0.09	0.19	1.00
INVF	0.00	0.71	0.05	1.00
EDUS	0.03	0.67	0.16	0.44	1.00
PS	0.00	0.80	0.06	0.57	0.55	1.00
U	−0.19	0.03	−0.09	0.08	0.11	0.05	1

For details and descriptions, refer to Table A1.

represent descriptive statistics and correlation analysis, respectively. Table 1 reports that the mean value of the variables, the shadow economy is 29.83, the tax burden is 75.19, and GDP is 3.9, which indicates that as the economic performance is low, the shadow economy is high, and the larger the size of the tax burden. On the other hand, Table 2 reveals that the shadow economy, trade, and tax burden positively correlate with GDP and SDGDP, but their correlation is relatively weak with SDGDP as compared to GDP. Furthermore, it is detected that there is a negative correlation between institutional variables with GDP and SDGDP. Nonetheless, these correlations do not mean causation; therefore, a proper investigation is needed to explore these relationships.

In

Table 3. Impact of shadow economy on economic stability.

	(1)	(2)	(3)	(4)	(5)	(6)
GDP/SDGDP	GMM (GDP)	GMM (SDGDP)	FE (GDP)	FE (SDGDP)	RE (GDP)	RE (SDGDP)
SE	−1.0567 **	−0.3670 **	−0.1158 *	−0.2285 **	−0.0335 *	0.0254 *
	[0.447]	[0.165]	[0.063]	[0.102]	[0.019]	[0.015]
L.GDP	0.5235 ***
	[0.085]
L.SDGDP		1.0539 ***
		[0.096]
T	0.0534 *	0.0138	0.0392 ***	0.0397 *	0.0077 **	0.0054 **
	[0.029]	[0.010]	[0.013]	[0.021]	[0.003]	[0.003]
TAXB	−0.5450 ***	−0.1316 ***	−0.1124 ***	−0.0134	0.0134	0.0160
	[0.162]	[0.050]	[0.035]	[0.051]	[0.015]	[0.012]
GE	−2.0999 ***	−0.1261	−0.6038 ***	−0.6506 ***	−0.3291 ***	−0.0621 **
	[0.547]	[0.125]	[0.125]	[0.188]	[0.042]	[0.032]
FF	0.0342	0.0010	0.0651 ***	0.0678 **	0.0049
	[0.123]	[0.034]	[0.025]	[0.026]	[0.011]
ER	−0.2505 *	−0.0228		−0.0835 ***	−0.0642 ***	0.0270 ***
	[0.149]	[0.037]		[0.029]	[0.013]	[0.008]
ROL	−0.5609 **	−0.2222 **
	[0.231]	[0.085]
GCF			−0.0000 ***
			[0.000]
INVF						0.0073
						[0.007]
EDU			−0.0262
			[0.023]
PS				0.0689 **	−0.0138
				[0.031]	[0.009]
U						−0.0269
						[0.028]
Constant	157.0361 ***	35.7475 **	20.2296 ***	18.3031 **	14.7519 ***	−1.6533
	[43.209]	[13.901]	[3.858]	[7.025]	[2.125]	[1.531]
Observation	895	894	1274	973	973	960
R2			0.113	0.178
Adjusted R2			0.108	0.172
Instruments	21.0000	45.0000
Groups	83	83
AR (1)	0.0000	0.000
AR (2)	0.1310	0.0061
Sargan	0.1346	0.2625
F-Stats	0.0000	0.0000

The dependent variable is (GDP) and (SDGDP) standard deviation of GDP. L.GDP and L.SDGDP are the lag of GDP and the lag of SDGDP, respectively. For details, and descriptions, refer to Table A1. Standard errors are in parentheses, and * p < 0.1, ** p < 0.05, and *** p < 0.01 denote significance at 10%, 5%, and 1%, respectively.

, the validity of GMM estimators has been tested. The p-value of the Sargan test predicts that there is no issue of instrument over-identification while the autocorrelation test has been passed. The choice of a dynamic model has been justified as the coefficients of lagged dependent variable are significant across all specifications. Focusing on our variable of interest, we see that the coefficient of the shadow economy has been negatively significant across all specifications. One way to support this finding is that an increase in the shadow economy is at the cost of a decrease in the official economy, which means the growth of the shadow economy is an indication that laborers and businesses are switching from the official economy to the shadow economy; as a result, the shadow economy boosts while the formal economy shrinks.

Another possible justification could be that tax evasion and the absence of government regulations in the shadow economy attract entrepreneurs and other skilled laborers from the formal economy to join the shadow economy. In an official economy with taxes on businesses and incomes, entrepreneurs and laborers move to the shadow economy from the official economy to maximize profit as an entrepreneur and income as a labor. The large size of the shadow economy may cause a decrease in government revenue as many workers appear to be unemployed in official statistics even though their earnings from the shadow economy continue. The shadow economy can also contribute negatively to economic growth through the social security contribution channel because people may earn from a shadow economy and not declare themselves to the government as employed. Businesses that engage in the shadow economy are not paying taxes. As a result, government tax revenue can be decreased because of low tax income, which may also lead to a decrease in economic growth [42,46,54].

Similarly, in the case of trade (T), we see in Table 3 model (1) that trade plays a positive role in economic stability, which is in line with [55]. On the other hand, the tax burden harms economic stability [56]. Due to the tax burden, businesses have moved to the shadow economy; as a result, goods and services in the official economy get decreased and thus destabilizing the economic conditions. Similarly, government expenditure also negatively impacts economic conditions. One possible justification can be that sometimes misallocating government resources can affect economic development and crowd out private businesses. It was also found by [57] that government spending crowds out investment and negatively impacts economic growth. (ER) and economic growth have a negative association. It may be explained in the sense that depreciation in the exchange rate decreases GDP because it increases the country’s import bills, increases the trade deficit, and, most importantly, raises the debt burden. Combining all these factors leads to destabilizing the economy. According to [58], exchange rate depreciation decreases economic growth and performance.

On the other hand, financial freedom has no impact on economic performance. At the same time, the rule of law decreases economic stability. It may be due to increased regulations, forcing businesses and workers to conform. Therefore, they switched to the shadow economy, and as a result, the economic performance of the official economy decreased.

4.1. Shadow Economy in Saudi Arabia

In

Table 4. Impact of shadow economy on economic stability in the case of Saudi Arabia.

Dep (SDGDP)	Coefficient	Std. err.	t	p > t	[95% conf.]	[Interval]
SE	−1.8071	0.0998	−18.1100	0.0350	−3.0750	−0.5393
BD	0.2743	0.0207	13.2300	0.0480	0.0108	0.5378
LF	−5.6826	0.3376	−16.8300	0.0380	−9.9721	−1.3932
ECOF	−0.8809	0.0826	−10.6600	0.0600	−1.9307	0.1688
GI	0.6781	0.0662	10.2400	0.0620	−0.1632	1.5195
TAXB	−9.2481	1.4102	−6.5600	0.0960	−27.1664	8.6702
GS	0.1826	0.0196	9.3200	0.0680	−0.0664	0.4316
VA	−1.4542	0.1303	−11.1600	0.0570	−3.1094	0.2010
COC	−0.0798	0.0265	−3.0100	0.2040	−0.4169	0.2572
GEFF	0.4108	0.0561	7.3300	0.0860	−0.3015	1.1231
Constant	1246.67	150.36	8.29	0.08	−663.84	3157.18
F(10, 1)	163.38
Prob > F	0.0608
R-squared	0.9994
Adj R-squared	0.9933
Root MSE	0.13416

The dependent variable is (SDGDP) the standard deviation of GDP. The SE is the focal variable. In contrast, control variables include (BD), (LF), (ECOF), (GI), (TAXB), (GS), (VA), (COC), (GEFF). For details, and descriptions, refer to Table A1.

, we observe that the (SE) coefficient is negatively significant, suggesting an inverse association between the shadow economy and economic stability. In other words, the shadow economy reduces economic stability in Saudi Arabia, too. One of the possible reasons for this negative impact is that many businesses and laborers working in the shadow economy are not revealing their income from the informal sector or second source of income to the government system. As a result, the stability of an economy weakens, and the shadow economy boosts.

Figure 5 relates to the average mean of the shadow economy in Saudi Arabia from 2004 to 2015. It is revealed from the graph that the average mean shadow economy in Saudi Arabia has reduced during the stipulated period. The Kingdom has increased its attempts to combat the shadow economy. The decrease in shadow activities has come after multiple laws were enacted, which aimed to make sure that businesses are conducted in the Kingdom legally and with the appropriate permits in order. The hidden economy magnitude equals 20% of the Kingdom’s GDP (GDP). The shadow economy in Saudi Arabia makes up a sizable portion of the domestic workforce, especially expatriates who may not be officially registered. Official labor force statistics exclude these workers employed in the unofficial sector. The introduction of digital transactions also assists the Kingdom’s general socio-economic growth. The rise in digital payments has improved financial inclusion, created more job opportunities, reduced shadow activities, and promoted economic growth.

4.2. Robustness Check

We have employed two types of robustness tests to check the consistency of estimated coefficients, i.e., using different methods and alternative proxies, i.e., model (1) to model (6) in

Table A2. Impact of shadow economy on economic stability (Alternative Variables and models).

	(1)	(2)	(3)	(4)	(5)
Dep. Var. GDP/SDGDP	FE GDP	FE SDGDP	RE GDP	GMM GDP	GMM SDGDP
SE	−0.2285 **	−0.0992 **	−0.0335 *	−1.0567 **	−0.3832 **
	[0.102]	[0.049]	[0.019]	[0.447]	[0.173]
L.SDGDP					0.5235 ***
					[0.085]
L.GDP				0.0045
				[0.095]
T	0.0397 *	−0.0166 *	0.0077 **	0.0534 *	0.0221 **
	[0.021]	[0.010]	[0.003]	[0.029]	[0.008]
TAXB	−0.0134	−0.0070	0.0134	−0.5450 ***	−0.1382 ***
	[0.051]	[0.028]	[0.015]	[0.162]	[0.048]
GE	−0.6506 ***	0.0857	−0.3291 ***	−2.0999 ***	−0.0217
	[0.188]	[0.072]	[0.042]	[0.547]	[0.164]
FF	0.0678 **	0.0152	0.0049	0.0342	−0.0297
	[0.026]	[0.015]	[0.011]	[0.123]	[0.030]
GCF		−0.0000 **
		[0.000]
EDU		−0.0126
		[0.016]
ER	−0.0835 ***		−0.0642 ***	−0.2505 *	−0.0137
	[0.029]		[0.013]	[0.149]	[0.034]
PS	0.0689 **		−0.0138
	[0.031]		[0.009]
ROL				−0.5609 **	−0.2574 ***
				[0.231]	[0.081]
Constant	18.303 **	6.1414 **	14.751 ***	157.036 ***	38.440 ***
	[7.025]	[2.785]	[2.125]	[43.209]	[13.882]
Observation	973	1273	973	895	894
R2	0.178	0.016
Adjusted R2	0.172	0.011
Instruments				21	53
Groups	83	133	83	83	83
AR (1)				0.00	0.00
AR (2)				0.13	0.015
Sargan				0.13	0.00
Hansen				0.54	0.01
F-Stats				0.00	0.00

The dependent variable is (GDP) and (SDGDP) standard deviation of GDP. L.GDP and L.SDGDP are the lag of GDP and the lag of SDGDP, respectively. All the other variables include (SE) shadow economy, Trade (T), Tax Burden (TAXB), (GE), (FF) Financial Freedom, (ER) exchange rate, (GFC) Gross Capital Formation, (INVF) Investment Freedom, (EDU) education, (PS) Political Stability and (ROL) Rule of Law. For details and descriptions, refer to Table A1. Standard errors are in parentheses, and * p < 0.1, ** p < 0.05, and *** p < 0.01 denote significance at 10%, 5%, and 1%, respectively.

. Firstly, along with GMM, we have employed fixed effect (FE) and random effect (RE) and found consistency in coefficients regarding signs and significance. Secondly, we have used two proxies for economic stability, i.e., GDP growth and standard deviation of GDP. In both cases, we noticed consistent coefficients across all specifications.

5. Conclusions

Shadow economy is the market value of all the unregistered final goods and services produced in the economy. At the same time, economic stability can be achieved through long-run continued economic growth. Selected studies focus on the drivers of economic stability or factors that push up the economic development of an economy. Alongside this, there is a pressing need to conduct more scholarly investigations considering the linkage between the shadow economy and economic stability. So, the primary objective of this paper is to analyze the impact of the shadow economy on economic stability by a set of econometric models. This study has covered 141 countries and a special case of Saudi Arabia from 2004 to 2015 and employs the GMM model and related robustness tests.

Our estimation results suggest that the shadow economy is negatively associated with economic stability in the case of the full sample and a special case of Saudi Arabia. Our findings reveal that the shadow economy hinders the government’s ability to fund public infrastructure and improve societal welfare, significantly reducing tax revenue. Our results confirm those of previous studies, such as [59,60,61]. In other words, the size of the shadow economy matters in destabilizing the official economy [41].

Considering our results, we recommend more all-encompassing steps to tackle the shadow economy. These actions include easing administrative and regulatory burdens, fostering good governance, enhancing tax compliance, streamlining processes, and fostering electronic payments. The development of effective electronic payment systems via more prepared financial institutions will be able to lessen the shadow economy. Future studies can consider all the countries in the world and employ a panel quantile model. Moreover, our insights should stimulate further studies on the interaction between the formal and informal economic sectors in the post-COVID-19 period. These could serve as novel ideas for further investigation.

In line, our study has significant policy implications in light of Saudi Vision 2030, which aims to create significant attention for policymakers to gauge the impact of shadow activities on the Saudi economy. The authorities should promote sectoral development and diversification and enhance the supervisory framework, which shall lessen the shadow activities in the Kingdom. Furthermore, the central bank of the Kingdom should accelerate the pace of contactless payments and provide more licenses to the non-bank payment service providers, which shall increase the ratio of non-cash consumer payments and thereby go a long way to reduce the shadow activities in the Kingdom. Moreover, we suggest using e-government tools in the toolbox of measures to combat the shadow economy, which would aid the government’s ability to meet the 2030 vision targets. Further, the e-government measures shall also facilitate coordination between different government levels agencies. This would improve bureaucratic performance, government integrity, and the general effectiveness of policies and shall be a powerful tool to limit the shadow economy [35].