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The purpose of this study is to analyze the relationship between public spending, budget imbalance and underground economy. In addition, this paper investigates how budget imbalance moderates the public spending–underground nexus.

By utilizing a data set spanning from 1995 to 2017 of 35 OECD countries, the study has employed Dynamic Common Correlated Effects (DCCE) approach. The study is also extended to consider the marginal effects of public spending on the underground economy at different degrees of budget imbalance.

The results indicate that an increase in public spending and budget imbalance contributes to the expansion of underground economy. Interestingly, the effects of public spending on the underground economy will enhance and intensify with a higher budget imbalance level. The results are robust to various specifications and their broader implications are discussed.

Governments should carefully implement a fiscal policy with a clear understanding that increasing public spending leads to the expansion of informality. Besides, policymakers should enforce supportive policies to boost economic growth, cooperation and cross-border trade to control the size of the underground economy.

This study stresses the role of public spending, budget imbalance on the underground economy in OECD nations. To the best of the author's knowledge, this study pioneers to explore the moderating effect of budget imbalance in the public spending–undergrround nexus.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0645.

In the presence of informal sector in the country, designing an energy policy and the pursuit of higher economic growth become challenging for emerging economies. These economies are usually resource starved, and the presence of underground economy leads to faulty estimates of energy demand. The authors explore the energy–growth nexus in the presence of underground economy for Pakistan, an emerging economy host to large informal sector and facing recurring energy crises.

The authors evaluate the impact of underground economy on energy demand in the presence of explanatory variables, including official gross domestic product (GDP), foreign direct investment and financial development. The authors first assess the influence of official economy on the consumption of energy. The authors investigate how energy consumption is influenced solely by underground economy. Finally, the authors evaluate the impact of true GDP on the energy consumption. The authors employ combined cointegration method of Bayer and Hanck (2013) and then apply vector error correction model.

The results reveal that official GDP, underground economy and true GDP positively and significantly affect energy consumption in both short and long run. Similarly, financial development as well as foreign direct investment enhance energy consumption. The authors find unidirectional causality between energy consumption and official GDP variables (OGDP → EC), underground economy (UE → EC) and true GDP variables (TGDP → EC) in the long run. The authors observe bidirectional causality in the short run between energy consumption and official GDP (OGDP ↔ EC) and true GDP (TGDP ↔ EC).

To the best of the authors' knowledge, no study examines the causal relationship of energy consumption and underground economy. Overall, the findings assist policymakers to consider and implement different energy-related policies considering the significant role of underground economy for energy consumption in Pakistan.

To measure the size of underground economy and the amount of tax evasion in Cyprus by employing monetary and non‐monetary approaches over the period 1960‐2003 and to compare the Cyprus figures with some European experience existing in the literature.

Annual data covering the 1960‐2003 period were applied to several approaches for measuring the size of underground economy and the amount of tax evasion in Cyprus. These approaches are: employment discrepancy; simple currency ratio; transaction and currency demand.

On the basis of the results obtained from this study: firstly, in Cyprus the average ratio of the underground economy and tax evasion to official GDP is estimated at 9.41 and 0.31 percent of GDP respectively for the study period, and secondly, in the two time intervals where Cypriots figures are internationally comparable with the often quoted EU underground economy figures, the figures for Cyprus are estimated as 5.96 percent of GDP in 1994‐95 and 5.67 percent of GDP in 1996‐97 whereas the figures for some European Union (EU) members are 18.05 percent of GDP in 1994‐95 and 18.76 percent of GDP in 1996‐97.

Findings of this study suggest that the issue of the underground economy is still in need of further investigation, firstly, to reach reliable results since each approach has its own strengths and weaknesses and yield different results, secondly, to find out the best method selection on a well‐established theory, and finally, to employ reliable data estimating measurement.

Both EU and Cypriot authorities can utilize this study to analyse the extent of Cypriot underground economy with respect to the other EU members. Such attempts can be useful in developing policies and implementing actions and measures to eliminate underground economy activities.

This study is the first of its kind with recent data to measure the size of underground economy and tax evasion for the Cypriot economy by employing various approaches.

Underground logistics system (ULS) is recognized as sustainable alleviator to road-dominated urban logistics infrastructure with various social and environmental benefits. The purpose of this study is to propose effective modeling and optimization method for planning a hub-and-spoke ULS network in urban region.

Underground freight tunnels and the last-mile ground delivery were organized as a hierarchical network. A mixed-integer programming model (MIP) with minimum system cost was developed. Then a two-phase optimization schema combining Genetic-based fuzzy C-means algorithm (GA-FCM), Depth-first-search FCM (DFS-FCM) algorithm and Dijkstra algorithm (DA), etc. was designed to optimize the location-allocation of ULS facilities and customer clusters. Finally, a real-world simulation was conducted for validation.

The multistage strategy and hybrid algorithms could efficiently yield hub-and-spoke network configurations at the lowest objective cost. GA-FCM performed better than K-means in customer-node clustering. The combination of DFS-FCM and DA achieved superior network configuration than that of combining K-means and minimum spanning tree technique. The results also provided some management insights: (1) greater scale economies effect in underground freight movement could reduce system budget, (2) changes in transportation cost would not have obvious impact on ULS network layout and (3) over 90% of transportation process in ULS network took place underground, giving remarkable alleviation to road freight traffic.

Demand pairs among customers were not considered due to lacking data. Heterogeneity of facilities capacity parameters was omitted.

This study has used an innovative hybrid optimization technique to address the two-phase network planning of urban ULS. The novel design and solution approaches offer insights for urban ULS development and management.

Using state-level data on productive and unproductive entrepreneurship, shadow economy size, and public official corruption, the purpose of this paper is to examine whether formal sector productive (unproductive) entrepreneurial activity is associated with lower (higher) levels of informal economic activity.

Additionally, the author aims to connect US state-level entrepreneurship, shadow economy size, and corruption by asking whether corruption affects entrepreneurial outcomes primarily through its effects on the shadow economy. The author contends that if this is the case, then estimates of corruption should serve as a good instrument for shadow economy size in regressions on formal sector entrepreneurial outcomes.

Results from OLS regressions suggest that shadow economy size shares a strong, negative (positive), and statistically significant relationship with productive (unproductive) entrepreneurship. These results are fairly robust to GMM estimation. Additionally, the author finds that corruption is a strong instrument for shadow economy size; one for which validity cannot be rejected in regressions on productive, and net entrepreneurship scores.

However, the author cannot safely assert that the author finds evidence of the shadow economy serving as a primary channel through which corruption affects observed entrepreneurial outcomes. Failure to reject validity of the corruption instrument is, at best, suggestive of the primacy of the entrepreneurial choice between formal and informal sector participation.

This study, to the author’s knowledge, is the first to attempt “connecting the dots” between entrepreneurship, corruption, and shadow economy size.

The purpose of this paper is to integrate the global value chain (GVC) perspective with firms' innovation in emerging economies (EEs) and explain why EE firms can improve their innovation capabilities more from their domestic markets by focusing on R&D and marketing than from original equipment manufacturer/original design manufacturer (OEM/ODM) modes in the GVC and how they contribute to the national innovation system (NIS).

The literature on GVC is reviewed and then several propositions are developed using the example of the underground mobile phone developers in China by integrating the GVC perspective.

The paper proposes that EE firms, especially firms that have a large underdeveloped domestic market such as China, should focus on R&D and marketing instead of on OEM/ODM in GVC to increase their competitiveness and strengthen their NIS. Also implications are drawn from their success in the underground markets to advance knowledge on NIS.

The paper shows that EE firms can build and strengthen their innovation capabilities through intense interaction and learning in domestic markets, which, subsequently, moves them upwards in their GVC. Industrial policy needs to change in order to facilitate such technological entrepreneurship in NIS, whether it is informal or underground.

The purpose of this paper is to review studies focusing on the magnitude of money laundering and their effects on a country’s economy. The relevant concepts are identified on the basis of discussions in the literature by prominent scholars and policy makers. There are three main objectives in this review: first, to discuss the effects of money laundering on a country’s macro-economy; second, to seek measurements from other scholars; and finally, to seek previous findings about the magnitude and the flows of money laundering.

In the first part, this paper outlines the effects of money laundering on macroeconomic conditions of a country, and then the second part reviews the literature that measures the magnitude of money laundering from an economic perspective.

Money laundering affects a country’s economy by increasing shadow economy and criminal activities, illicit flows and impeding tax collection. To minimise these negative effects, it is necessary to quantify the magnitude of money laundering relative to economic conditions to identify the most vulnerable aspects of money laundering in a country. Two approaches are used in this study: the first is the capital flight approach, as money laundering will cause flows of money between countries; the second is the economic approach for measuring money laundering through economic variables (e.g. tax revenue, underground economy and income generated by criminals) separately from tax evasion.

The paper offers new insights for the measurement of money laundering, especially for developing countries. Most methods in quantifying money laundering have focused on developed countries, which are less applicable to developing countries.

Despite the vulnerability of rapidly developing and emerging market economies, researchers have paid less attention to the determination of the size of money laundering (ML) in these economies, including the United Arab Emirates (the UAE). Therefore, this paper aims to estimate the magnitude of ML in the UAE between 1975 and 2020 based on the currency demand approach (CDA).

The study uses the Gregory–Hansen cointegration technique alongside the autoregressive distributed lag bounds testing procedure to estimate the CDA model.

The results illustrate that an amount equivalent to about 19.034% of the GDP is laundered in the UAE between 1975 and 2020, on average, with the value lying between 15.129% and 23.121%. In addition, the results demonstrate the importance of the real estate market, gold trade, remittance channels and the size of the underground economy in facilitating the laundering of illicit funds in the country.

To the best of the authors’ knowledge, the study is the pioneering attempt at estimating the amount of illicit funds laundered in the UAE. Besides, the adoption of a novel, yet robust, approach based on the modification of the CDA technique also sets the study apart as it ensures a correct, clear, unambiguous and indisputable estimate of the magnitude of ML is obtained. In addition, it is expected that the outcome of the study will expand the frontiers of knowledge among policy makers and relevant agencies and ensure the adoption of the most efficient and effective measures to curb the ML menace in the country.

This paper aims to define a new system for detecting money-laundering activities by comparing tax payments (especially value-added tax) data to banking transactions data.

A money laundering detection (MLD) system provides the necessary bases for detecting deception and fraud. Though MLD is a complementary system of the Rastin Banking system, it can also be installed and executed separately.

The underground economic activities can be detected and traced by comparing banking information and transaction information in MLD system. It needs to force the direct transactors or other related forms of transaction to perform their money operations through the banks. In the next step, the tax information of transactors (in a chain of transactions) can be compared with them, and the incompatibility of the two sets of data will explore money-laundering operations.

This system is novel and needs to be more elaborate to remove further practical problems and specific cases.

MLD system provides necessary protection for those who perform legal economic activities by detecting financial criminals.

Money laundering harms individual and public rights as well as economies. Financial crimes, tax evasion, smuggling, conspiracy, embezzlement and various other offences are included in the general definition of money laundering, so detecting them will lead to important economic improvements in the society as well as international community.

MLD system provides structural and electronic bases for computerized tax data and banking data comparison.