We empirically address the effects of monetary policy on the housing market in China using a novel Time-Varying Parameter VARX model. We show that an expansionary monetary has positive effects on the housing market, while during COVID-19, the effects are approaching to zero or even negative. In addition, the effects of the LPR policy are strong and even larger than that of COVID-19. Relative impulse response functions in the shorter and longer time horizons are dynamic and especially during COVID. This paper also contributes to the housing literature to show that COVID-19 can block the transmission of monetary policy.

The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.

In this paper I will show that budget deficit (or fiscal deficit) is necessary to achieve full employment under constant prices or inflation, using a model of endogenous growth in which consumers hold money for the reason of liquidity and live forever. Budget deficit need not be offset by future budget surpluses. I consider the continuous time case by taking the limit of the discrete time case when the time interval approaches zero. A continuous time dynamic model seems to be more general than a discrete time model. When the actual budget deficit is greater (smaller) than the value which is necessary and sufficient for full employment under constant prices, an inflation (a recession) occurs. The main argument of this paper is that a growing economy requires the continuation of budget deficit, and that we should not think of paying off the resulting government debt with taxes.

Motivated by the Blackorby-Schworm (1993) observation that market outcomes may differ from those originating in market-actor optimization, this paper claims that the number of banks in the market is larger than the number justified by bank profit maximization alone or in combination with bank depositor welfare maximization. This claim is made within the context of bilateral monopoly banks and intertemporal utility maximization by bank depositors. The basic policy implication towards bank population rationalization is a minimization of the deviation away from the optimal interest rate margin at every stage of the business cycle. It is meant to be an acyclical policy though the target of optimal bank population is attainable by active countercyclical policy as well. The nature of this policy issue makes the use of macroprudential measures imperative, jointly perhaps with a fiscal-monetary policy mix. A dynamic version of the model in a Cournot environment is akin to the modeling of Minsky's hypothesis of financial fragility.

I examine the problem of budget deficit in a growing economy in which consumers hold money as a part of their savings in the case where consumers live forever. For simplicity and tractability I use a discrete time dynamic model and Lagrange multiplier method. In the appendix I briefly explain the solution using a discrete time version of the Hamiltonian method. I will show the following results. 1) 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, balanced budget cannot achieve full employment under constant prices. I do not assume that budget deficit must later be made up by budget surplus.

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.

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.

Even though policy coordination is one of the oldest challenges that governments have to confront, as problems evolve and "New Public Management" concepts emerge, it has become even more essential. The current literature on policy coordination among government agencies, however, shows little regarding the way coordination is managed under centralized political systems. This study, based on the science and technology (S&T) policy documents issued by China's central government agencies between 1978 and 2020, provides a quantitative and dynamic analysis of the coordination of policies in China and presents a comprehensive overview of policy coordination paths and processes in centralized political systems. As a result, it provides a way that contributes to the analytical methods available for quantitatively analyzing policy documents. On the other hand, the key findings of the study show that, first, state council-administered ministries have taken the lead in coordinating policy while other types of organizations have collaborated in more subordinate capacities. Second, national themes that are democratic and driven by demand have been the core concern of coordination activities, such as social development, high-tech industrialization, and rural S&T. Third, policy coordination has evolved continuously and has mostly contributed to interpreting macrostrategies and implementing more specific implementation measures.

Generating output growth by adding more inputs into the production process may not be sustainable in the long run for any economy, given the limited resources. On the other hand, if productivity growth dominates the production process, it will generate more output without excessive increase in input use. Hence, this paper examines whether the output growth in Indonesia’s manufacturing sector is excessive inputs driven or productivity driven. Productivity driven growth is measured by Total Factor Productivity (TFP) growth, which is decomposed into its major components of technological progress and technical efficiency within the framework of varying coefficients stochastic frontier analysis (VSFA) using Indonesia’s annual Large and Medium Manufacturing Industries Survey data over the period 2002–2014. The measurement of the components of TFP growth not only provides more insights and better understanding of the dynamic nature of the production processes, but also has important policy implications. The mean TFP growth during the period 2002-2014 was estimated to be 4.3 per cent and was mostly contributed by technological progress experienced by firms. The policy implication is that technical efficiency could still be improved for the selected technology to reap the full benefit of increasing output from the chosen technology.

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.

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 rise of privately issued digital currencies, which primarily serve as alternative investment assets poses a challenge to the traditional financial instruments traded in the financial market. This study examines the dynamic relationship between the major privately issued digital currency (Bitcoin) and two financial market securities in Nigeria. The paper employed Vector Autoregressive (VAR) model and presents three relevant findings. First, the impulse response function indicates the absence of a significant response of the Nigerian financial market to shocks emanating from the Bitcoin market, implying lower connectedness between the two markets. Secondly, the outcome of the variance decomposition reveals a lower contribution of Bitcoin to changes in stock prices and treasury bills, however, stock prices and treasury bills contributed higher impact to each other compared to the contribution of Bitcoin. Thirdly, a weak bi-directional causality between the Bitcoin and treasury bills was observed and a uni-directional causality running from treasury bills and stocks, implying the existence of portfolio rebalancing from the fixed income to the equities market. Despite the weak connection between digital currency and the financial market, the paper recommends that the Central Bank of Nigeria and the Securities and Exchange Commission should maintain monitoring the development of crypto exchanges and continue reviewing the existing policy restricting cryptocurrency transactions through banks to avoid its unsavoury effects.

Green innovation, driven by China's new development concept, plays a crucial role in high-quality economic development. In line with the green development trend, businesses increasingly prioritize whether their corporate environmental responsibilities (CER) can effectively enhance corporate green innovation (CGI) levels. This paper examines the influence and mechanism of CER on CGI using a dynamic perspective, drawing from 1,640 manually-collected panel data of Shanghai and Shenzhen A-share listed companies between 2010 and 2017. The primary findings indicate that the impact of CER on CGI possesses phase-specific characteristics and a dual effect of "crowding in" and "crowding out." The current phase of CER negatively affects green innovation, while the lag phase has a positive effect. CER's impact on various CGI types is heterogeneous: specifically, it follows an "inverted-N" trajectory (inhibition-promotion-inhibition) for "strategic green innovation" and has a promotional effect on "substantive green innovation," which is stronger and has a longer time lag. The mechanism analysis reveals that financing constraints play a critical mediating role. A heterogeneity analysis based on multiple dimensions (ownership, industry, and location) suggests that CER has a more significant driving force for CGI among state-owned firms, high-polluting industries, and enterprises in inland areas. Finally, the paper presents corresponding suggestions for government and corporate entities.

The dynamic patterns of technology adoption among firms clustered by size are investigated to assess the implications arising from the digital divide. Using data from the “Survey on the Use of Information and Communication Technologies in Enterprises (IUTICE)" dataset for 2003-2022, provided by the Portuguese Institute of Statistics, the research centers on three key variables – internet connectivity, website presence, and computer usage – which are examined across a spectrum of firms’ scales, shedding light on the evolving trends in technology adoption. Employing a combination of descriptive statistical analysis, trend assessment, and cross-sectional comparisons, this research shows noteworthy insights. Interestingly, the adoption rates for all three technology variables exhibit a consistent upward trajectory, indicative of a movement towards digitalization within the business landscape. Smaller firms have demonstrated notable strides, manifesting a reduction in the technology adoption disparity relative to their larger counterparts. The findings underscore the influential roles played by resource constraints and digital competencies in shaping technology adoption trajectories, and their correspondence with the Resource-Based View (RBV) framework underscores the role of organizational resources and capabilities on the digital divide. The ramifications extend beyond individual firms, resonating with the global scholarly discourse and advocating for equitable integration of technology. As firms, irrespective of size, grapple with the challenges posed by the digital era, this study provides deep insights that can guide the formulation of strategies aimed at cultivating an inclusive and technologically empowered business environment.

The manufacturing sector must incorporate digitalization and greening as crucial strategies to attain high level of development in the context of the digital economy, given its significant role in quality of environment. Most of existing studies explore net effect of a single or several factors on the digitalization or greening in the manufacturing industry. Limited investigation has been done to integrate various factors impacting the connection and synchronized advancement of digitalization and greening within the manufacturing. Factors affecting the synergy of digitalization and green change within manufacturing are recognized in this article, and a theoretical framework is established to analyze. FsQCA tool is also put into use to survey configurational cases, which contains synergy degree of green digitalization from 30 provinces’ manufacturing in China. Results show that: (1) Between 2007 and 2020, the development level of digital-green integration in the manufacturing industry shows an upward trend. There are three types of collaborative modes, namely, "industrial robot driven" "market development driven" and "market development driven - industrial robot driven", with each mode consisting of at least one to four equivalent pathways. (2) The marketization level and application of industrial robots are the important external and internal pulling forces that drive the synergy degree of digitalization and green change within manufacturing industry, respectively.(3) The influencing factors of the collaborative mode choice of digital-green development within manufacturing industry are complementary, among which, the degree of marketization is similar to the role of industrial robots in the configuration, which are capable to weaken the negative impact from insufficient government R&D investment support under specific conditions; (4) The non-high collaborative state of digital green in manufacturing industry is mainly due to the low level of marketization, openness, and economic development, as well as the low application rate of industrial robots and software products. This study enriches the theoretical understanding on digitalization and green change of manufacturing industry. Meanwhile, it also provides insights to advance the integrated and synergistic advancement of digital green transformation in manufacturing practice.

All things being equal, and in a truly democratic world, one will expect that the fact that women are the majority in almost every single community of the world should guarantee them at least equal control or ownership over resources and enjoy most of the rights and privileges in that particular community. But things seem not to be working that way as evidence from the literature shows that women are always relegated to the background when it comes to the issue of control or ownership over, and sometimes even access to property in most societies which include the right to own and use land. This undoubtedly has a consequence on the productive and overall development of such a community. In recent times, the issue of gender discrimination, disparities, and inequalities has attracted the attention of researchers over the past decade with enormous literature in this area. There are, however, few studies that provide a comparative analysis of the situation between two or more countries. This paper seeks to fill this void of knowledge based on a review of relevant literature on land rights with an emphasis on the situations in Kenya and Tanzania. The results have shown the prevalence of four types of land rights such as communal property rights, non or open-access property rights, state or crown property rights, and private property rights. The results have further indicated that the controversial land rights of Kenya have led to the reduction in the lands of certain groups of people, increasing land disputes, and also discriminating against women in their land rights. In the case of Tanzania, there were several cases of bias against women concerning the ownership of land, especially under the customary system of Tanzania. Issues of discrimination against women were also identified in the inheritance laws of the land which is a paramount feature within the norms and cultures of the people of Tanzania. The lack of equal access to land by women in both countries is found to harm productivity in several sectors of their economies, especially in agriculture. Policymakers are therefore admonished to ensure equal access by both genders to land as this will lead to efficiency in the management and usage of land which is certainly good for sustainability in the development of any economy.

Population, as a fundamental element in urban development, often reflects a city's economic development pattern through its spatial distribution and dynamic changes. Studying population spatial distribution is pivotal for bolstering the economic activity capacity in urban agglomerations and guiding regional economic health. Using the Changsha-Zhuzhou-Xiangtan urban agglomeration as a case study, this paper analyzes its overall spatial structure and the spatiotemporal evolution of population at the district and county levels. This analysis utilizes population density, population redistribution index, and population geographic concentration as key indices. Additionally, a spatial econometric model is constructed to assess the impact of economic, social, and environmental factors on population spatial patterns. Findings reveal several key points: (1) Furong District serves as the primary central area, boasting a population geographic concentration of 25.1% in 2021. Tianxin District, Kaifu District, Yuhua District, Shifeng District, Yuelu District, and Hetang District constitute the secondary central areas, while Yutang District, Tianyuan District, Lusong District, Yuhu District, Wangcheng District, and Changsha County form the tertiary level areas. (2) Population density within the Changsha-Zhuzhou-Xiangtan urban agglomeration gradually decreases from Furong District outward. The first central area and sub-central areas experience increasing population density, highlighting a polarization trend in the population distribution. (3) The overall Moran's index for the spatial distribution of population in the Changsha-Zhuzhou-Xiangtan urban agglomeration is significantly positive, indicating a strong spatial autocorrelation and a deepening spatial agglomeration of population distribution. (4) Per capita disposable income, financial expenditure, and education level positively influence the geographical concentration of population in the urban agglomeration, while GDP per capita, road area per capita, and environmental quality exert a negative impact. Notably, the most influential factors shaping population spatial distribution are GDP per capita, disposable income per capita, and air quality.

Approximately 28 million individuals in the United States face the risk of developing precancerous colonic adenomas (polyps) and potentially progressing to colorectal cancer (CRC). While a promising strategy for CRC prevention involves pharmacological intervention, such as cancer chemoprevention or interception, currently, there are no FDA-approved drugs capable of preventing the formation or progression of adenomas to adenocarcinoma. Numerous clinical, epidemiological, and preclinical studies have offered compelling evidence supporting the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) in CRC chemoprevention. However, the prolonged use of NSAIDs is not FDA-approved due to potential life-threatening toxicities resulting from cyclooxygenase (COX) inhibition and the depletion of physiological prostaglandins. Despite indications that the COX inhibitory activity of NSAIDs may not be essential for their antineoplastic effects, the absence of a well-defined target impeded the development of derivatives that do not inhibit COX. Earlier research suggests that the inhibition of cyclic guanosine monophosphate phosphodiesterase (cGMP PDE) may be responsible, at least in part, for the antineoplastic activity of the NSAID sulindac. This could potentially offer a novel target for CRC chemoprevention. To identify the cGMP PDE isozyme(s) contributing to the antineoplastic activity of sulindac, we synthesized a chemically diverse library of over 1500 compounds, all sharing the indene scaffold of sulindac. Subsequently, we screened these compounds for their impact on cancer cell growth and PDE inhibitory activity. From this screening, a series of lead compounds emerged. These compounds lacked COX-1 and COX-2 inhibitory activity, surpassing sulindac in potency to inhibit CRC cell growth. Importantly, they demonstrated greater selectivity by not affecting normal cell growth. Through chemical optimization, we identified several development candidates that selectively inhibit PDE5 and/or PDE10. These compounds activate cGMP/PKG signaling, suppressing Wnt/β-catenin transcription. This action counters the growth advantages resulting from APC or CTNNB1 mutations, which are responsible for most human CRCs. This review delves into the scientific literature supporting PDE5 and/or PDE10 as potential targets for CRC chemoprevention or interception. Our findings suggest a promising avenue for developing drugs that may effectively intervene in the progression of colorectal cancer, offering hope for improved preventive strategies in the future.

Background: Hepatocellular carcinoma (HCC) stands out as one of the most lethal cancers globally, given its complexity, recurrence following surgical resection, metastatic potential, and inherent heterogeneity. In recent years, researchers have systematically elucidated the significance of long non-coding RNA (lncRNA) in the initiation and progression of HCC. The introduction of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases has significantly enhanced the prognostic assessment of HCC. However, the association between HCC and cell senescence has been infrequently explored in the literature. Method: We downloaded liver hepatocellular carcinoma (LIHC)-related messenger RNA and lncRNA expression levels from TCGA. Correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to validate the lncRNA risk model associated with cellular aging. Comparing the infiltration of diverse immune cells enabled the identification of distinct differences in the immunological microenvironments of the two risk groups. Subsequently, we conducted a real-time polymerase chain reaction (qPCR) experiment to confirm the accuracy of the selected lncRNAs. Results: A predictive framework for HCC was constructed based on the expression levels of five lncRNAs. Multivariate and univariate Cox regression analyses revealed that lncRNA signatures associated with senescence were independently correlated with an increased risk of HCC. Additionally, the nomogram also provides a more refined and sensitive model. Further investigation into the variations in immune cells and functions between the high-risk and low-risk groups was conducted. Subsequently, a qPCR experiment results revealed underexpression of AC068756.1, AC090578.1, AC145343.1, and LINC0022 in Huh7 and LM3 cells. In contrast, AP003392.4 did not exhibit a significant difference between Huh7 and control cells. Conclusion: The prognostic features and nomogram, consisting of five aging-related lncRNAs (AC068756.1, AC090578.1, AC145343.1, AP003392.4, and LINC00221), may be useful in predicting the overall survival of HCC.