Economic complexity and shadow economy: A multi-dimensional analysis

Ha, Le Thanh; Hoang, Dung Phuong; Thanh, To Trung

doi:10.1016/j.eap.2021.09.011

Cited by 22 publications

(17 citation statements)

References 66 publications

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“…, 2014). Complexity as an alternative concept of the economic system, also called productive knowledge, has been coined by Ha et al. (2021) and Hidalgo and Hausmann (2009) to measure a country's stock of knowledge.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Is economic complexity an enabler of environmental innovation? Novel insightful lessons from European region

2023

MEQ

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PurposeThis paper empirically examines the influences of economic complexity performance on environmental innovation implementation.Design/methodology/approachThe research is based on four measures designed to assess the effectiveness of environmental innovations in 24 European countries, including the percentage of enterprises implementing environmental innovation investment (% of surveyed firms), the percentage of enterprises implementing environmental innovation activities (e.g. implementation of resource efficiency actions, sustainable products or ISO 14001 certificates) measured, a number of enterprises having new ISO 14001 registration and a number of environmental innovation related patents. After conducting various tests for longitudinal correlations and asymmetry of the studied series, we examine the relationship between product proximity, economic complexity and environmental innovation (EI) implementation using the panel-corrected standard error model (PCSE) model in the following section. The feasible generalized least squares (FGLS) model is employed to further verify our findings by taking into account heteroscedasticity. An application of the two-step generalized mixed model (GMM) is considered to resolve an endogeneity issue. In addition, the dynamic fixed-effects estimate (DFE) estimator is applied to the autoregressive distributed lag (ARDL) method in order to calculate both the short-run and long-run effects. As indicated by Ha (2022a, b) and Ha and Thanh (2022), the DFE-ARDL method can be used to identify both time-fixed effects and country-fixed effects.FindingsThe authors provide empirical evidence to propose the mechanism through which economic complexity encourages the implementation of environmental innovation through favorable impacts of economic complexity on environmental innovation investments of firms and governments and the public's awareness regarding the importance of environmental innovations.Practical implicationsThis research provides important implications for policymakers in promoting environmental innovations.Originality/valueThe study is the first to empirically examine economic complexity performance's influences on environmental innovation implementation. It is also the first to investigate the importance of institutional quality in enhancing the influence of economic complexity on environmental performance.

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Is economic complexity an enabler of environmental innovation? Novel insightful lessons from European region

2023

MEQ

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“…In general, these included variables are cross-sectionally dependent, and some variables are not stationary, but their first-level difference becomes stationary. Based on these properties of our database, we follow Beck and Katz (1995), Ha et al 2021a;Ha 2022b, Ha andThanh (2022), and Le and Hoang (2021) to employ the PCSE model for our sample. All explanatory variables are lagged by one period, as represented in Eq.…”

Section: Control Variablesmentioning

confidence: 99%

“…Digitalization has a beneficial effect on both social behavior and economic advancement. Economists have shown that increasing digitalization adoption may boost growth (Myovella et al 2020;Solomon and van Klyton 2020), decrease income inequality (Ha 2022a), promote financial development (Ha 2022a), and even diminish the size of the shadow economy (Ha et al, 2021a). Digitalization, according to the few studies that have addressed this perspective, is related to income levels (Ha and Thanh 2022), economic complexity Ha and Thanh (2022), institutions (Le and Nguyen 2019), and financial development (Ha 2022a).…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic and resource efficiency impacts of digital public services

2022

Environ Sci Pollut Res

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This paper measures the socioeconomic and resource-efficient influences of digital transformation in the public sector in the European region. To capture the socioeconomic impacts of digital public services, we employ a socioeconomic score index calculated as the unweighted average of the re-scaled scores for changes in employment, exports, and turnover from ecoindustries. Regarding resource-efficient impacts, we employ the resource efficiency score index measured as the unweighted average of the re-scaled scores for material, energy productivity, and the intensity of greenhouse gas (GHG) emissions. Measures such as user-centricity, business mobility, and key enablers are used to demonstrate the level of digitalization in the public sector. According to our estimations based on various econometric techniques, digital public services have a favorable effect on the economy and society through a positive impact on employment, exports, and turnover of eco-industries. The effects of digitalization on resource productivity follow a nonlinear U-shaped curve, suggesting that the improvement of resource efficiency is only present when the digital transformation process reaches a certain level.

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“…To investigate the effect of AfT ows on the shadow economy, we build on the previous literature on the drivers of the shadow economy (e.g., Berdiev and Saunoris, 2018;Berdiev et al, 2018a;Berdiev et al, 2018b;Berdiev et al, 2020;Canh and Thanh, 2020a,b;Nguyen, 2022;Ha et al, 2021;Kelmanson et al, 2019). We consider a baseline model speci cation where the dependent variable is the indicator of the shadow economy (denoted "SHADOW"), and the main variable of interest is the indicator of AfT ows (denoted "AfT").…”

Section: Model Speci Cationmentioning

confidence: 99%

Do Aid for Trade Flows Help Reduce the Shadow Economy in Recipient Countries?

Gnangnon

2022

Preprint

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The present analysis has assessed the effect of Aid for Trade (AfT) flows on the shadow economy using an unbalanced panel dataset of 106 countries over the period from 2002 to 2015. Empirical results obtained by means of the two-step system generalized method of moments, show that higher AfT flows are associated with a fall in the size of the shadow economy, with less developed countries experiencing a greater negative effect of AfT flows on the shadow economy than relatively advanced countries among recipient countries of AfT flows. AfT interventions reduce the size of the shadow economy in countries that face high trade costs as well as in those that experience a depreciation of the real exchange rate. Finally, AfT interventions reduce the size of the shadow economy in countries that improve the economic complexity level.JEL Classification: F14; F35; O17.

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Economic complexity and shadow economy: A multi-dimensional analysis

Cited by 22 publications

References 66 publications

Is economic complexity an enabler of environmental innovation? Novel insightful lessons from European region

Is economic complexity an enabler of environmental innovation? Novel insightful lessons from European region

Socioeconomic and resource efficiency impacts of digital public services

Do Aid for Trade Flows Help Reduce the Shadow Economy in Recipient Countries?

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