This study employs a multi-sector computable general equilibrium (CGE) model to investigate the German-Russian trade relationship, with an emphasis on the effects of sanctions on Russian imports following Ukraine's invasion. The input-output (I-O) table from 2015 is used in the study to quantify the impact of these restrictions and the changes in Germany's production that follow. Various counterfactual scenarios are explored, which includes quota of 67% and 35% on energy and rest of the Russian imports respectively, as well as 30% ad-valorem tariff. The simulation of this quota scenario on the baseline model shows significant reductions in output and domestic use levels. Additionally, the counterfactual analysis of the 30% ad-valorem import tariff on Russian imports indicates a 1.7% overall price increase and a roughly 3.8% decrease in household welfare due to the sanctions.
Because it establishes connections between nations that are both enduring and stable, foreign direct investment, or FDI, is an essential component of global economic integration. The connection between FDI and economic expansion has long been a significant issue worldwide. Using econometric analysis, this study examines the impact of FDI on India's economic growth from 1991 to 2022 and other important parameters like trade openness, inflation rate, government expenditure, domestic investment, human capital, and international crisis. Economic growth is positively impacted by trade openness, government spending, domestic investment, and human capital, according to the empirical findings. On the other hand, economic growth is negatively impacted by the inflation rate and international crisis, which are statistically insignificant. By including the effects of FDI-led economic growth on poverty alleviation and income distribution, the study also suggests a future research direction.
An important risk in the actuarial industry is the longevity risk, therefore the as accurate as possible prediction of mortality rates is very crucial. Such predictions are performed by modelling the mortality rates using mortality models and predicting the future mortality trends. Aiming at possible improvements of such forecasts, we examine the effect of data transformation-'linearisation' on the quality of time series forecasts of mortality, using data resulted from mortality models for England-Wales. By time series 'linearisation' is meant the treatment of causes that disrupt the underlying stochastic process. Results indicate a clear improvement for interval forecasts of mortality. However, the result for point forecasts is not as clear. The documented improvement in interval forecasts can significantly affect the solvency capital requirement, rendering some pension providers at a competitive advantage. It was also confirmed that the transformed-linearised series satisfy better the need for normality as compared to the original series.
We examine the relationship between taxation and economic growth using several tax variables for a sample of OECD economies over the period 1980-2020. Our dynamic panel GMM threshold model follows the spirit of Seo and Shin (2016), hence we can trace nonlinearities in the taxation-growth nexus following recent theoretical developments. We unmask a statistically significant inverted 'U-shaped' relationship between effective tax rates and economic growth justifying a more efficient reformulation of public policy toward tax reforms. Further, the mixed evidence surrounding the effects of different tax indicators suggests that a one-size-fits-all approach may not be effective. Instead, tailored tax policies that account for the unique economic contexts of different countries, especially within the OECD framework, could lead to more effective economic outcomes.
The present paper explores the impact of budget balance shocks, as well as output shocks, on the current account balance of four high-income Southeast Asian countries, namely China, Japan, Republic of Korea and Singapore. For performing this analysis, a panel structural VAR model has been implemented, using an extended sample of a more than 40-year period. The estimated impulse-response functions and variance decompositions for common and idiosyncratic shocks provide an indication regarding the way that fiscal and output shocks affect the current account balance. In brief, they imply that, in the short run, the twin divergence hypothesis holds. In other words, an expansionary fiscal policy will improve the current account balance. However, in the long run, the empirical evidence seems to validate the new classical Ricardian equivalence theorem.
This study aims to discover financial associations (relations) in (foreign) exchange rates, cryptocurrencies, and stocks using association rule mining (ARM). It demonstrates the applicability and success of ARM on alternative investment instruments over desired periods. A dynamic web application called 'Finassociations' was developed in this scope, allowing investors to use and discover ARM. They can use the desired filters to make investment decisions by generating rules for which investment instruments rise or fall together. The application dynamically retrieves current data from Yahoo Finance. This study is a dynamic and expanded update on the existing ones. The exemplary analyses utilised data spanning various periods, up to two years preceding October 9, 2022. According to the study results, significant and strong financial associations in three different investment groups can be obtained. Also, the results show that short-term financial data can be preferred over long-term financial data when examining associations between investment instruments.
We examine the competitiveness of Greek agri-food exports during the Greek debt crisis. We employ the Balassa revealed comparative advantage (RCA) index and the Vollrath revealed competitiveness (RC) index. Changes in RCA and RC trends together with panel vector autoregression analysis (PVAR), allow us to discuss the dynamic relation of competitiveness and GDP and infer on policies to strengthen Greek agri-food trade. Results show that Greece has a revealed comparative advantage in many agri-food product categories, however, the 2009 debt crisis led to significant losses in competitiveness. Economic policy should target vegetable and foodstuff products to ensure quick recovery of competitiveness in the international markets.
In this paper, we investigate the potential impact of social cohesion on the level of economic activity in European Union countries for the 2001-2022 period. Following a macroeconomic approach, we consider the effect of inequality on economic activity using income per capita, competitiveness, public debt and deficit and monetary policy as control variables. For the whole period under investigation, we observe that all but one (competitiveness) explanatory variables are statistically significant, also bearing the expected sign. Particularly interesting, though, is the strong and positive relationship between inequality and unemployment. Even more interesting though is that we observe a change in the effect of inequality on unemployment before and after the 2007-2009 crisis when during that second period inequality became the most significant determinant of unemployment, while in the pre-crisis period it was insignificant. Our approach supports the rekindled interest placed on inequality as an important factor affecting social welfare after the great recession.
This paper provides an efficient approach for approximating the Black-Scholes (B-S) model with a market price jump spread term for European put and call options using orthogonal Gegenbauer polynomials (OGP) and time derivative estimation. Therefore, we formulate a genuine and speedy numerical calculation technique that is grounded on the established convergence recovery method. The derivative matrix of a OGP polynomial is obtained through this polynomial property. Using the numerical method has an advantage in speed and efficiency, as the orthogonality of OGP polynomials and operational matrices decreases calculation time. To validate the validity of the new procedure, it presents two problems and provides numerical analyses that explain its efficiency and accuracy.
This study explores the relationship between corporate social responsibility (CSR) and firm financial performance, focusing on how board composition influences this link. It examines how governance features of the board of directors support stakeholder interests and align with strategic company goals. The analysis uses the feasible generalised least squares (FGLS) estimator, an advanced econometric method that corrects for heteroscedasticity and serial correlation to produce reliable estimates. The study analyses a panel of 349 European firms from 2011 to 2021, measuring CSR through environmental, social, and governance (ESG) scores and their key dimensions. Results show a significant positive association between CSR and financial performance, measured by return on assets and equity. Board characteristics such as size, independence, and gender diversity strengthen this relationship, while chief executive officer (CEO) duality weakens it. These findings highlight the critical role of sound corporate governance in maximising the value created by CSR initiatives.
The foreign exchange (forex) market's efficiency has significant implications for investment decisions, risk management, and economic policies. This paper investigates the efficiency of the Indian forex market during financial upheavals, focusing on the Hurst exponent a measure from fractal theory analysis, as a tool to analyse the self-similarity and predictability of price trends. Using data from four major exchange rates (USD, GBP, EUR and JPY) against the Indian rupee, spanning 2018 to 2021, the study employs the application of the Hurst exponent, and changepoint analysis to assess the forex market's efficiency during financial upheavals, such as the COVID-19 pandemic. The study contributes to the understanding of market efficiency dynamics, offering practical implications for traders, investors, policymakers, and businesses dealing with foreign exchange rates. By bridging theoretical insights with empirical findings, this research aids decision-makers in navigating the complexities of the ever-changing landscape of international finance.
This study examines the influence of the Russia-Ukraine conflict on the relationship between wheat prices and the stock markets of the G7 countries, employing the DCC-GARCH model with daily data spanning from January 1, 2020, to September 29, 2023. The results reveal a significant negative shock in the dynamic conditional correlation between wheat and the stock markets analysed, particularly in France, Germany, and Italy. These findings suggest that wheat can serve as an effective tool for mitigating portfolio risk. This research sheds light on the effects of geopolitical events on the dynamics of financial markets, especially in advanced economies. The findings have important implications for both portfolio management and policy formulation. Investors in stocks and commodities may benefit from the policy insights provided by this study, which could assist them in making informed investment decisions during periods of heightened volatility.
This paper investigates the effectiveness of 11 automatic time-series forecasting techniques in forecasting the wholesale price index (WPI) of potatoes in India. Techniques include autoregressive integrated moving average (ARIMA), error-trend-seasonality (ETS), four artificial neural network (ANN) models, and five hybrid approaches. Evaluation is based on mean absolute percentage error (MAPE). The forecast horizon extends up to 15 months. This work revealed that the ETS-ANN method is the most effective, showcasing an average MAPE of 5.42%. The improvement of the forecast accuracy of the hybrid ETS-ANN over the naive (baseline) is 59.8%, ETS is 29.18%, and ANN is 41.85%. It indicates a significant enhancement in forecast accuracy. The ETS-ANN approach exhibited statistically significant results. It validates the ETS-ANN technique's effectiveness in accurately forecasting the potato WPI in India. It contributes to this specific domain and provides valuable insights for policymakers and stakeholders. Additionally, it may serve as a methodological guide for other agricultural commodities.
