We propose an open-access innovation index for the U.S. states. This index was built by classifying into four core areas the twelve more important indicators, inputs, and outputs, that are widely accepted in the literature as the most relevant for measuring innovation. We consider the indicators aggregated in the areas of human capital and business environment as the inputs that create knowledge and influence the promotion of innovation, while those in areas of engagement and efficiency as the outputs that are all those outcomes and improvements related to the innovation process. As an example of potential uses of our index, we ran a basic econometric experiment using the economic growth rate as the dependent variable. Despite the results being qualitatively consistent with the literature, we suggest further research using our index and other methodologies. We included in the appendix the overall index score and ranking from 2000 to 2015.

This study documents the relationship between economic freedom and unauthorized immigration to the U.S.A. and tries to answer a still-in-debate question, what motivates people to unauthorizedly migrate? Using the generated instrument variables methodology, and a data panel of 15 countries and 16 years, the endogenous variable is the gap in economic freedom between the country of origin and the U.S., and the dependent variable is the unauthorized immigrant’s growth rate. The results show that for each 10% improvement in economic freedom in the country-of-origin unauthorized immigration decreases around 7%. Estimations are robust even after using other covariates and external instruments. The main conclusion is that economic and social factors play a significant role in shaping migration patterns and that the difference in economic freedom between the country of origin and the U.S. plays a fundamental role in deciding to unauthorizedly migrate

The use of digital technologies like artificial intelligence, robotics, or smart devices can be expected to go hand in hand with higher productivity and lower trade costs, and, therefore, to be positively related to export activities. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union to shed further light on this issue by investigating the link between the digitalization intensity of a firm and extensive margins of exports. We use a new machine-learning based regression method, Kernel-Regularized Least Squares (KRLS), which effectively handles non-linear relationships in models and does not impose any restrictive assumptions for the functional form of the relation between margins of exports, digitalization intensity, and any control variables. We find that firms which use more digital technologies do more often export, do more often export to various destinations all over the world, and do export to more different destinations.

We examine the relationship between labour market flexibility, as measured by employment protection legislation (EPL), and long-term economic growth in developed economies from 1995 to 2022. We consider conflicting viewpoints on whether rigid labour market regulations hinder or promote economic growth. Employing a cross-country regression model, controlling for factors including initial GDP per capita, capital formation, human capital, research and development, and indicators of macroeconomic performance, we find that only initial income level and capital formation significantly influence long-run growth in real per capita GDP. EPL has no significant impact in the long run, challenging the pre-2000 advocacy of labour market deregulation by major international organisations. We conclude that policy should focus on supporting the investment decisions of the private sector without distorting market mechanisms.

Nigeria, as an import-dependent economy, has seen its inflation rate rise over the years, which might be ascribed to structural causes and imported consumer products. The Autoregressive distributed lag model was used to determine the competitiveness of domestic and foreign prices. In the short run, domestic and international pricing complement each other, but in the long run, they may achieve some level of competitiveness. The currency rate has a considerable and beneficial impact on consumer spending. The result could also be explained by customers' high desire for foreign items.

This paper employs a two-way fixed effects model and uses panel data from 31 provinces of China between 2012 and 2022 to empirically analyze the impact of digital inclusive finance on China's Outward Foreign Direct Investment (OFDI). The study finds that, overall, the development of digital inclusive finance in China significantly promotes OFDI. Its sub-dimensions, including coverage breadth and usage depth, have a significant positive impact on OFDI across Chinese provinces. Further analysis reveals that the sub-dimensions of usage depth, such as credit and payment, also have a significant effect on OFDI in various provinces. In addition, the control variable of economic development level significantly positively influences OFDI in China. Regional regression results indicate that the development of digital inclusive finance in central and western China significantly promotes OFDI in these regions, while the effect is not significant in the eastern region. Policy Recommendations: China should accelerate the development of a digital inclusive finance system and promote financial innovation. It is crucial to focus on the coordinated development of various digital inclusive finance indicators, narrow the financial service gap between regions, and thus foster the long-term development of China's outward foreign direct investment.

Green finance is an important driving force to promote green innovation and achieve green development. In order to deeply explore the internal relationship between green finance and green innovation efficiency, this paper selects China's provincial panel data from 2012 to 2023, uses the entropy method and super efficiency SBM model to measure the green finance development index and green innovation efficiency of each province, and on this basis, chooses to construct the spatial Durbin model with fixed effects for empirical analysis and effect decomposition. The results show that: (1) From 2012 to 2023, the development level of green finance and green innovation efficiency of China's provinces will increase year by year with the development of economic base; (2) The green innovation efficiency of provinces with better economic foundation and perfect infrastructure is also at a high level; (3) The level of green finance development, productivity, fiscal revenue and expenditure and urbanization not only have a direct effect on the green innovation efficiency of the region, but also have a spatial spillover effect on the neighboring regions.

Recently, some authors have found derivations and applications of the golden ratio in economics science. Based on previous models of Financial Gravity (FG) and generalizing them, this paper proposes the maximization of pure flows after charges as a way for applying the golden ratio in the sales-costs of production ratio in competitive equilibrium, leading to an optimal unitary charge of 0.2361… with many economic applications in monetary economics as well as in finance, public economics and taxation, migration flows, VAT on goods and services and commercial trading. Other applications are also suggested for further research. This paper can be useful for mathematical and applied economists, public financiers, bankers and policy and lawmakers.

This paper shows mainly the following results. 1) The debt to GDP ratio cannot diverge to infinity, that is, fiscal collapse is impossible. The necessary condition for this result is that the propensity to consume from the asset is positive. 2) The divergence of the debt to GDP ratio is prevented by inflation when the interest rate on government bonds is considerably higher than the real growth rate, and the inflation rate which is sufficient to prevent divergence of the debt to GDP ratio is smaller than the interest rate on government bonds. Only an inflation rate slightly greater than the difference between the interest rate on government bonds and the sum of the real growth rate and the propensity to consume from the asset is required. This inflation is not caused by policy but occurs naturally.

We assess the impact of the Strategic Economic Plan on Singapore’s long-term GDP per capita. To our knowledge, we are the first to evaluate the effect of the 1991 plan on Singapore’s successful growth trajectory using methodologies aimed at causal identification. In other words, this article applies the Synthetic Control method and World Bank data from 1970 to 2018. We estimate an average increase of 6,641.71 US$ in Singapore’s GDP per capita. Results remain robust to placebo and leave-one-out tests and the Synthetic Difference-in-Differences method.

This study considers the effects of disclosure conditions on firms' investment decisions when facing an identical competitor in multiple markets. Assuming that there are congestion costs between multiple investments to reduce marginal cost for each market, this study focuses on the cases where the disclosure conditions may differ by market. Like previous studies on single Cournot competition, these results show that firms invest more in the observable investment markets than in the unobservable markets under symmetric disclosure conditions. However, firms invest more in the unobservable market if there are asymmetric disclosure conditions.

In this study, the time-varying pattern of returns with the trading cost is assessed in light of sanctions on the Russia’s economy. The analysis is performed on the Moscow Exchange Index (MOEX) using the ordinary least squares (OLS) method, Bayes’ Theorem technique, and vector error correction model (VECM). Firstly, the transparency of asset’s value in the same trading period was noted to execute the trade with a limited price impact. Thus, the liquidity seems not priced in returns. In addition, the posterior probability of the transparent asset’s value stabilized the market at a limited transaction cost. In this case, there is less likelihood of liquidity acting as a risk element in returns during the same trading session. These results correspond to the era without sanctions, as well as economic restrictions period. Before the economic restrictions, the execution of investment occurred on its real or close value due to the market transparency in the following trading period. This implies, that the past trading cost series is not priced in yields on investment. During the Russia-related sanctions, a higher price impact of transaction was noted due to the ambiguity in the future asset’s value. Therefore, the past liquidity series is a pricing element in the short run and long run. The analysis suggests a potential inference of trading cost to determine the yield on investment.

This study empirically examines the influence of corporate financialization on trade credit financing, focusing on non-financial companies listed in China's A-share market from 2010 to 2022. The results indicate that as corporate financialization increases, companies will obtain less trade credit financing. Further incorporating moderating factors like market position and financing constraints, we find that a higher market position effectively mitigates the negative impact of corporate financialization on trade credit financing, whereas higher financing constraints exacerbate the adverse effects of corporate financialization on trade credit financing. Additional analysis shows that corporate financialization negatively affects trade credit financing by crowding out main business performance and increasing operational risks. Moreover, corporate financialization more strongly inhibits trade credit financing in state-owned companies.

This work investigates the strength and the pattern of linkages among the three markets of qualitatively differentiated milk (i.e., conventional, organic without heymilk, and organic with heymilk) in Austria using the flexible TVP-VAR frequency connectedness approach and information on prices from 2018 to 2023. The main empirical findings are: (a) Taken together, the markets have maintained a moderate degree of connectedness to each other.  (b) Price linkages have been frequency-dependent; much of the adjustments to incoming information have been completed within 3 months. (c) Connectedness has been asymmetric; the highest quality (organic with heymilk) has been a net transmitter of price shocks to organic without heymilk. (d) The intensity of connectedness has been time-varying; however, the internal structure of the market network (i.e., the net transmitters and receivers of price shocks) has remained fairly stable.

The current study examines the performance of 76 Japanese equity Exchange Traded Funds (ETFs) over the period 1/1/2018-12/31/2022. Performance is estimated in several ways, that is, raw returns, alphas from single- and multi-factor regression models, and risk-adjusted returns. The market timing skills of ETF managers are examined too. The results reveal that, on average, the examined ETFs do not produce any material alpha. The results also indicate that the risk factors suggested by Fama and French (1993 & 2015) are more or less capable of explaining the performance of the Japanese ETFs. Finally, the findings show that 21% of ETF managers possess some sort of market timing skills. However, the managers fail to time the volatility of the stock market.

Spence’s signaling model (Spence, 1973) suggests that education can signal workers’ unobserved ability to employers thereby mitigating discrimination. There have been several studies concerning education’s impact on labor market discrimination against minority or disadvantaged groups. Our approach in this inquiry is unique in that we utilize the data of PhD recipients, a group of people with the highest education attainment, to test Spence’s theory. Another novelty of this paper is that in addition to examining possible discrimination against women and foreign-born, as has been done in previous studies, we further explore possible discrimination against the physically challenged individuals. Our baseline results show conflicting results that Ph.D. education can reduce discrimination against disability and foreign-born but not against gender. Further analysis by the Blinder-Oaxaca Decomposition shows that the wage gaps of gender and disability come more from the unobserved part than the explained part, while the foreign-born wage gap come more from the observable human capital differences. Since prejudice is an unobserved factor and we know that the disadvantaged groups are likely to suffer from prejudice (Oaxaca, 1973; Blinder, 1973; Montes-Rojas et al., 2017; Deshpande and Khanna, 2018), we conjecture that prejudice might be attributable to the unexplained part of the wage gaps. Furthermore, prejudice might be deeply rooted in one’s mind, thus difficult to remove even with the influence of education. Hence, our results reveal that it would be hard for Ph.D. education to eradicate the discrimination against gender and disability, but not against foreign-born.

The objectives and tasks of the European Central Bank (ECB) are defined in Articles 2 and 3 of Protocol (No 4) on the Statute of the European System of Central Banks (ESCB) and of the European Central Bank (ECB). While in Article 3,1° of this Protocol other tasks are mentioned, the prime objective of the ESCB and therefore of the ECB, is price stability. This concept was originally specified by the Executive Board of the ECB as an annual increase of less than 2% in the inflation rate over the medium term, measured by the Harmonized Index of Consumer Prices (HICP) for the euro area. This paper examines to what extent the ECB has been effective in realizing price stability over the period from January 1, 2000 to December 31, 2022. Price stability is important for economic agents. It allows them to plan their savings, spending and investment eventually resulting in sustained economic growth.   Notwithstanding the commitment of large human and other resources and the use of unconventional monetary policies, the ECB did not realize its prime objective during a large part of this period. We conclude that putting too much confidence in DSGE-modeling as one of the methodologies to determine monetary policy, may have played an important role in the ECB not achieving its main statutory objective.

The precise prediction of carbon emissions trading prices is the foundation for the stable and sustainable development of the carbon financial market. In recent years, influenced by a combination of factors such as the pandemic, trading regulations, and policies, carbon prices have exhibited strong random volatility and clear non-stationary characteristics. Traditional single-perspective prediction methods based on conventional statistical models are increasingly inadequate due to the homogenization of features and are struggling to adapt to China's regional carbon emissions trading market. Therefore, this paper proposes a multi-perspective fusion-based prediction method tailored to the Chinese market. It leverages carbon emissions trading information from key cities as relevant features to predict the price changes in individual cities. Inspired by the development of artificial intelligence, this paper implements various time series models based on deep neural networks. The effectiveness of the multi-perspective approach is validated through multiple metrics. It provides scientific decision-making tools for domestic carbon emissions trading investors, making a significant contribution to strengthening carbon market risk management and promoting the establishment and rational development of a unified carbon market in China.

Vector Error Correction Models (VECM) have become a standard tool in empirical economics for analyzing nonstationary time series data because they integrate two key concepts in economics: equilibrium and dynamic adjustment in a single model. The current standard VECM procedure is limited to time series data with the same degree of integration, i.e., all I(1) variables. However, empirical studies often involve time series data with different de‐grees of integration, necessitating the simultaneous handling of I(1) and I(0) time series. This paper extends the standard VECM to accommodate mixed I(1) and I(0) variables. The conditions for the mixed VECM are derived, and consequently, we present a test and estimation for the mixed VECM.

Foreign direct investment (FDI) is widely viewed as a key driving force behind China’s exceptional growth performance in the last four decades. This paper investigates several questions posed by China’s success in capturing gains from FDI. What explains that success? Can other countries replicate it, or is it unique to China? What lessons are from China for other countries? China indeed has advantages in attracting FDI such as huge market and cheap labor, the well-designed policy and strategy, however, seem to play more important role in the successful story. Our empirical estimates support on four hypotheses: FDI and GDP growth in China positively interact each other; FDI is helpful to China’s technological progress, FDI promotes China’s industrial development, and FDI stimulates China’s manufactured exports.