This paper presents an operational framework for assessing the trajectories of production, energy, emissions, and capital accumulation to ensure the implementation of Nationally Determined Contributions (NDCs). The framework combines widely used methodologies (STIRPAT, system dynamics, and optimization) to simulate the pathways of variables until a target year. The CO-STIRPAT dynamic system allows us to identify the spillover pathways from carbon policy to economic growth based on output optimization principles; to conduct a more systematic analysis of the interconnections between the main drivers that determine carbon emissions; to develop a cost-effective climate policy mix that is a backbone for the right combination of carbon pricing, energy efficiency, and carbon intensity; and to assess NDC targets with respect to ambition gaps, implementation gaps, and feasibility.

We present two approaches to forecasting parameters in the SABR model. The first approach is the vector autoregressive moving-average model (VARMA) for the time series of the in-sample calibrated parameters, and the second is based on machine learning techniques called epsilon-support vector regression (ε-SVR). Using daily data of S&P 500 ETF option prices from January 1, 2014, to December 31, 2018, we first calibrate the daily values of the model parameters from the training sample, then conduct out-of-sample forecasting of parameters and pricing of options. Both approaches produce good fits between the forecasted and calibrated parameters for out-of-sample dates. A comparison study shows that using forecasted parameters as inputs, the SABR model generates better pricing results than assuming constant parameters or using lag parameters. We also discuss the market conditions under which one approach outperforms the other.

Understanding the economic trends and demographic dynamics of a country is crucial for policymakers and researchers to formulate effective strategies and policies. This study aims to examine the GDP trends and aging index dynamics in Portugal from 2011 to 2021, with a focus on regional disparities and their implications for demographic challenges. The findings highlight the relationship between regional GDP and the aging index, indicating that regions with higher GDP values tend to have a relatively younger population, while regions with lower GDP values have a relatively older population. The study contributes to the existing literature on population aging by providing insights into the demographic, economic, and social implications of an aging society. It provides valuable insights into the demographic, economic, and social implications of population aging in Portugal. The findings contribute to the existing literature and can inform policymakers and stakeholders in developing targeted strategies and policies to address the specific challenges faced by each region.

The sensitive nature of interest rate has spurred empirical interests on the factors that determine it. This paper examined the joint impact of exchange rate and foreign direct investment inflows on interest rate in Nigeria over the period from 1981-2022. The study made use of the auto regressive distributed lag (ARDL) bounds test and results of findings reveal that in both the short-run and the long-run the impact of the interaction between FDI inflows and exchange rate on real interest rate was negative and significant. Also, while credit to the private sector was found to have significant positive impact on real interest rate in both the time horizons, the impact of consumer price index was negative only in the short. Oil revenue was found to impact positively on real interest rate only in the long-run, but the impact of broad money supply was negative and significant in both the short-run and the long-run. The study suggests that policies to regulate domestic interest rate should focus on joint regulation of both exchange rate and FDI inflows and this requires a synergy between monetary and fiscal policies.

Rental unaffordability is defined as spending more than 30% of a household’s gross income on rent. Post-pandemic inflation and interest rate increases have intensified rental unaffordability. This research examines rental affordability in the U.S., the U.K., and Canada. It also explores the effect of renters’ “affordability knowledge” – defined as the expertise tenants have and use to make economical rental housing choices – on rent expenditure and affordability positioning and compares personal finances, economic perspectives, and demographics based on renters in affordable and unaffordable situations. The results show that nearly two-thirds of the renters studied are in unaffordable rental situations. Interestingly, affordability knowledge was found to reduce rent spent and increase affordability situations. Significant demographic differences were found between those in affordable and unaffordable rental situations, including rent spending, food spending, transportation spending, savings, perceived homeownership likelihood, and age. The research offers important insight into current rental affordability economics, recommendations for policymakers, and opportunities for real estate organizations.

This paper attempts to introduce an overlapping generations structure into Paul Krugman's "The world's smallest macroeconomic model" (Krugman (1999)) to examine the implications of fiscal policy, particularly fiscal deficits, in a framework suitable for policy analysis. In that paper, Krugman argued that under the price rigidity assumption, a shortage in the money supply leads to underemployment and recession, so increasing the money supply would eliminate underemployment and restore full employment. But how can the money supply be increased? I show that in order to restore full employment out of a recession, a fiscal deficit is needed to increase the money supply. I also show that in a growing economy, fiscal deficits are necessary to maintain full employment at constant prices or inflation. Fiscal deficits are not only effective in pulling the economy out of recession, they are even necessary for growth to continue without recession or inflation. The fiscal deficit in this paper represents the difference between government spending and government revenues. If this difference is positive, we say that the government is in deficit. Krugman's original model is a one-period static model. I intend to extend this model to a dynamic overlapping generations model.

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.

Traditionally, conditions of sustainability of the public debt have long been related quite exclusively to fiscal policy and to budgetary parameters. However, the interaction between fiscal and monetary policies regarding the fixation of the interest rate is fundamental. Indeed, a simple analytical modelling shows that if the nominal interest rate increases exponentially with the public debt, because of a default (credit) risk premium, if the confidence of investors is fundamental, conditions of sustainability of the public debt could be much more difficult to comply with. Indeed, if the interest rate is risk-free, values for which the public debt can be sustainable are less constraining if the long-term GDP growth rate is high, or if the long-term risk-free nominal interest rate is small. They are also less constraining if the country decides to turn to a non-negligible primary budget surplus in case of a high public debt. However, if the interest rate exponentially increases with the public debt level, in case of a significant importance of the default (credit) risk premium, these parameters have very limited consequences on sustainable and equilibrium public debt levels. The sustainable public debt that a government should target is then much smaller than in absence of this risk premium.

The policy of ethnic equality and solidarity aims to narrow the ethnic gap and develop harmoniously. At the level of higher education, it should promote the equity of ethnic education. This paper uses the administrative data of undergraduate students from 2008 to 2015 in a liberal arts university in southwest China to study the differences, causes and dynamic trends in the scores of college students from different nationalities. The results show that compared with Han students, the average GPA of ethnic minority students is 0.13 points lower (equivalent to 0.23 and 0.3 standard deviations of the scores of ethnic minority and Han students), the fourth grade scores are 0.28 standard deviations lower, and 7.3% lower. This difference is more significant in the western region, especially in Xinjiang, Yunnan, Hubei and other provinces inhabited by ethnic minorities; Kazak and uygur are the nationalities with the biggest gap with han students; The difference between girls is more significant than that between boys. The "peer effect" and cultural distance between roommates are important reasons for this difference. Further analysis shows that although the ethnic differences in academic performance are gradually expanding, the growth rate tends to converge. The above conclusions are helpful to clarify the object and time of making national higher education policy, and also have important reference significance for primary and secondary education.

This research investigates the determinants of women's empowerment within households in a developing country. The investigation specifically focuses on the impact of employment and fertility, considering constraints imposed by family rules that play a pivotal role in shaping women's empowerment. The theoretical framework outlined in this study posits a simplistic model demonstrating that, within the prevailing family structure and household composition, earned income and fertility may bear significant relevance. Utilizing data extracted from the Pakistan Social and Living Standards Measurement Survey, we engage in estimating the level of female empowerment, operationalized as the extent of female authority over household expenditures. Notably, our empirical approach accounts for the endogeneity of employment and fertility through a two-stage estimation process. This involves leveraging information on family rules—representative of a family's cultural norms—pertaining to work and childbearing. Our empirical findings affirm the viability of family-specific rules as instruments to estimate and subsequently predict employment and fertility. Importantly, the evidence gleaned underscores the critical role of selecting valid threat options in theoretical analyses of women's empowerment.

By an endogenous growth model with a two-period overlapping generations structure, I examine the existence of a budget deficit in an economy that endogenously grows by investments of firms. The consumers leave bequests to their descendants and hold money as a part of their savings. I use a Barro-type utility function, where people include the utility of their children in their own utility. The main results are as follows. 1) A budget deficit is necessary for full employment under constant prices. 2) Inflation is induced if the actual budget deficit is greater than the value at which full employment is achieved under constant prices. 3) If the actual budget deficit is smaller than the value which is necessary and sufficient for full employment under constant prices, a recession occurs. Therefore, a balanced budget cannot achieve full employment under constant prices. I do not assume that the budget deficit must later be made up by a budget surplus. I use a Barro-type utility function to prove the necessity (or inevitability) of a budget deficit instead of the neutrality of government debt. In the appendix of this paper, I show that if money, as well as goods, are produced by capital and labor, a budget deficit is not necessary for full employment under constant prices.

Green-biased technological progress takes into account the influence of energy input and pollution emissions, which is of great significance to China's green development. This paper decomposes technological progress into two categories: green input-biased technological progress (IBTC) and green output-biased technological progress (OBTC), using the Slacks-based measure integrating (SBM) model. The factor bias in technological progress is determined based on data from 34 industries in China from 2000 to 2015. The results show that green-biased technological progress exists significantly in the industry, and most of it promotes the growth of green total factor productivity. IBTC first tends to consume energy to pursue capital between capital input and energy input, while it tends to save energy after the Eleventh Five-Year Plan. Between labor input and energy input, it is biased towards saving labor and consuming resources. OBTC is biased towards promoting industrial growth and curbing pollution emissions. Medium and light-polluting industries are biased toward promoting industrial growth and curbing pollution emissions, while heavy-polluting industries are biased towards emitting more pollution.

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 COVID-19 pandemic wreaked havoc on economies everywhere, affecting everything from supply chain networks to international trade as a direct result of the increased vulnerability of more nations and the disruption of the activities of key traders. This research study examines how COVID-19 affected the supply chain on a worldwide and regional scale, as well as the systemic policy and economic steps governments and businesses took to rebound and maintain resilience. COVID-19 has had a significant influence, prompting governments and businesses to take steps to fortify their operations and businesses against disruptions, highlight the necessity for resilience in supply chains and emphasize the importance of managing risk. The supply value chain is at risk from the prolonged implementation of COVID-19 trade measures like border closure, export restrictions, and import sanctions. Many businesses are transitioning from a "recovery mode" to a resilient and sustainable mode" and are beginning to plan for the future. The study suggests that corporate and government leaders should prioritize proactive and adaptable policy, economic, and structural adjustment. This research will be useful to policymakers and industry leaders in their efforts to lessen the effect of COVID-19 on the global supply chain by enforcing governmental, economic, and business reforms built on resilient supply chains and mitigating economic risks during tough times.

Digitalization is nowadays one of the fastest developing processes. The adoption of digital technologies can provide innumerous opportunities for the organizations to evolve and gain competitive advantage by leveraging of technologies to respond to dynamic expectations and demands. Information about the country digitalization level is essential to decision makers in both public and private organizations. It can present insights on which areas need the most investment, and furthermore to gain feedback on the outcomes of these investments. For companies, it can create a certain predictability on which products and services will be required the most. To assess the evolution of this process in different countries, various indexes were proposed and employed by different corporations. The Digital Economy and Society Index (DESI) and ICT Development Index (IDI) are used by public organizations. Digitalization Index (DiGiX) and Cisco Digital Readiness Index (CISCO) are used by private companies. Comparing two sectors highlights the most common factors of digital evaluation. Indexes are analyzed thoroughly by their structure, coverage, weights, methodology and ranking. The result of the practical work is a equivalence table which shows the percentage of their similarity. Additionally, a new digitalization index is proposed, based on the result of the previous comparison, which can be applied to analyze both public and private sector of the country’s digitalization level.

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.

The digital transformation of manufacturing industry can promote the development of green transformation and promote the differentiation of workers’ skill structure; On the other hand, it will also hinder the green development due to the huge energy consumption generated by the application of digital technology and facilities. In addition, the green transformation of manufacturing industry will also have differentiated impacts on the employment of labour with different skills due to the innovation of green technology. The existing research has not discussed too much about the interaction among the digital transformation and green transformation in manufacturing industry and labour structure. So, this paper uses the PVAR model to examine the dynamic relationship between digital and green transformation within the industrial sector from the perspective of labour structure, specifically analyzing the impact difference across regions. The results suggest that there is a reciprocal connection between the digitization of manufacturing sector and the labour structure, particularly in the eastern region of China, but the overall interaction between the two remains weak. The interactive between the green transformation of manufacturing industry and the labour structure in the central and western areas has been delayed over periods 1-6. Digital and green manufacturing transformation reinforce each other in central and western regions. However, the digital revolution in the manufacturing industry is hindered by the green transformation in eastern region.

The Weibull distribution is extensively useful in the field of finance, insurance and natural disasters. Recently, It has been considered as one of the most frequently used statistical distributions in modelling and analyzing stock pricing movement and uncertain prediction in financial and investment data sets, such as insurance claims distribution. It is well known that the Bayes estimators of the two-parameter Weibull distribution do not have a compact form and the closed-form expression of the Bayes estimators cannot be obtained. In this paper and the Bayesian setting, it is assumed that the scale parameter of the Weibull model has a gamma prior under the assumption that its shape parameter is known. A simulation study is performed using random claims amount to compare the performance of the Bayesian approach with traditional maximum likelihood estimators in terms of Root Mean Square Errors (RMSE) and Mean Absolute Error (MAE) for different sample sizes, with specific values of the scale parameter and shape parameters. The results have been compared with the estimated result via the maximum likelihood method. The result revealed that the Bayesian approach behaves similarly to the maximum likelihood method when the sample size is small. Nevertheless, in all cases for both methods, the RMSE and MAE decrease as the sample size increases. Finally, applications of the proposed model to the insurance claim data set have been presented.

Scientific and technological innovation and human capital savings are important ways to promote the high-quality development of China's economy. On this basis, using the panel data of 30 provinces in China from 2009 to 2017, this paper empathically tests the impact of university research activities on high-quality growth of China's economy, and explores the influence mechanism from two dimensions of talent cultivation and achievement transformation. Based on the spatial perspective, the regional heterogeneity of these influences is analyzed. This paper finds that: First, research and development activities in universities effectively boost the high-quality development of China's economy. Secend, the stimulating effect of university research and development on economic growth. On the one hand, through the talent training function of scientific research activities, it enriches the accumulation of human capital and drives the economic development; On the other hand, constrained by the predicament of scientific research achievement transformation, the stimulating effect of university scientific research activities on economic growth will be limited to a certain extent. Third, there are significant regional differences in the promoting effect of university research activities on high-quality economic development, and this difference may come from the spatial spillover effect of university research activities. This study has important enlightening significance to understand the relationship between university scientific research activities and high- quality economic development.

This study delves into the complex relationship between China's international trade and economic growth, specifically focusing on emission intensity and its environmental ramifications within the context of energy efficiency. The primary objective is to provide a comprehensive understanding of how China's international trade dynamics influence economic growth, emphasizing emission intensity and employing a model that considers the nonlinear impact of trade on output. Through this model, structural breakpoints are identified, revealing distinct outcomes for China amidst positive and negative shocks from 1972 to 2021. The study uncovers the dual nature of the energy sector, acting both as a source of environmental degradation and a potential avenue for positive change through increased efficiency. Complex interplays among economic activities, inflation, and investment on carbon intensity are revealed. Additionally, the varying effects of export volume on carbon emissions intensity across lag thresholds underscore the significance of global trade dynamics for environmental sustainability. The study concludes by emphasizing the importance of balancing economic prosperity with environmental responsibility, advocating for carefully balanced policies that foster sustainable growth. Recommendations include considering the dual nature of the energy sector and implementing policies promoting increased efficiency. Policymakers are urged to adopt growth models prioritizing environmental responsibility, balancing economic activities, inflation, and investment to mitigate carbon intensity while acknowledging the diverse effects of global trade dynamics on environmental sustainability.