Monthly Data Research Articles

Identifying time patterns of highland and lowland air temperature trends in Italy and the UK across monthly and annual scales

Abstract. This paper presents a statistical analysis of air temperature data from 32 stations in Italy and the UK up to 2000 m above sea level from 2002 to 2021. The data came from both highland and lowland areas in order to evaluate the differences due to both location and elevation. The analysis focused on detecting trends at annual and monthly timescales, employing ordinary least-squares (OLS), robust S-estimator regression, and Mann–Kendall (MK) and Sen's slope methods. Hierarchical clustering (HCA) using dynamic time warping (DTW) was then applied to the monthly data to analyze the intra-annual pattern similarity of trends within and across the groups. Two different regions of Europe were chosen because of the different climate and temperature trends – namely, the northern UK (smaller trends) and the northwest Italian Alps (larger trends). The main novelty of the work is to show that stations with similar locations and altitudes have similar monthly slopes by quantifying them using DTW and clustering. These results reveal the nonrandomness of different trends throughout the year and between different parts of Europe, with a modest influence of altitude in wintertime. The findings revealed that group average trends were close to the National Oceanic and Atmospheric Administration (NOAA) values for the areas in Italy and the UK, confirming the validity of analyzing a small number of stations. More interestingly, intra-annual patterns were detected commonly at the stations of each of the groups and are clearly different between them. Confirming the different climates, most highland and lowland stations in Italy exhibit statistically significant positive trends, while in the UK, both highland and lowland stations show statistically nonsignificant negative trends. Hierarchical clustering in combination with DTW showed consistent similarity between monthly patterns of means and trends within the group of stations and inconsistent similarity between patterns across groups. The use of the 12 distance correlation matrices (dcor) (one for each month) also contributes to what is the main result of the paper, which is to clearly show the different temporal patterns in relation to location and (in some months) altitude. The anomalous behaviors detected at 3 of the 32 stations, namely Valpelline, Fossano, and Aonoch Mòr, can be attributed, respectively, to the facts that Valpelline is the lowest-elevation station in its group; Fossano is the southernmost of the Italian stations, with some sublittoral influence; and Aonoch Mòr has a large number of missing values. In conclusion, these results improve our understanding of temperature spatio-temporal dynamics in two very different regions of Europe and emphasize the importance of consistent analysis of data to assess the ongoing effects of climate change. The intra-annual time patterns of temperature trends could also be compared with climate model results.

Fine Particulate Matter, Its Constituents, and Spontaneous Preterm Birth.

The associations of exposure to fine particulate matter (PM2.5) and its constituents with spontaneous preterm birth (sPTB) remain understudied. Identifying subpopulations at increased risk characterized by socioeconomic status and other environmental factors is critical for targeted interventions. To examine associations of PM2.5 and its constituents with sPTB. This population-based retrospective cohort study was conducted from 2008 to 2018 within a large integrated health care system, Kaiser Permanente Southern California. Singleton live births with recorded residential information of pregnant individuals during pregnancy were included. Data were analyzed from December 2023 to March 2024. Daily total PM2.5 concentrations and monthly data on 5 PM2.5 constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) in California were assessed, and mean exposures to these pollutants during pregnancy and by trimester were calculated. Exposures to total green space, trees, low-lying vegetation, and grass were estimated using street view images. Wildfire-related exposure was measured by the mean concentration of wildfire-specific PM2.5 during pregnancy. Additionally, the mean exposure to daily maximum temperature during pregnancy was calculated. The primary outcome was sPTB identified through a natural language processing algorithm. Discrete-time survival models were used to estimate associations of total PM2.5 concentration and its 5 constituents with sPTB. Interaction terms were used to examine the effect modification by race and ethnicity, educational attainment, household income, and exposures to green space, wildfire smoke, and temperature. Among 409 037 births (mean [SD] age of mothers at delivery, 30.3 [5.8] years), there were positive associations of PM2.5, black carbon, nitrate, and sulfate with sPTB. Adjusted odds ratios (aORs) per IQR increase were 1.15 (95% CI, 1.12-1.18; P < .001) for PM2.5 (IQR, 2.76 μg/m3), 1.15 (95% CI, 1.11-1.20; P < .001) for black carbon (IQR, 1.05 μg/m3), 1.09 (95% CI, 1.06-1.13; P < .001) for nitrate (IQR, 0.93 μg/m3), and 1.06 (95% CI, 1.03-1.09; P < .001) for sulfate (IQR, 0.40 μg/m3) over the entire pregnancy. The second trimester was the most susceptible window; for example, aORs for total PM2.5 concentration were 1.07 (95% CI, 1.05-1.09; P < .001) in the first, 1.10 (95% CI, 1.08-1.12; P < .001) in the second, and 1.09 (95% CI, 1.07-1.11; P < .001) in the third trimester. Significantly higher aORs were observed among individuals with lower educational attainment (eg, less than college: aOR, 1.16; 95% CI, 1.12-1.21 vs college [≥4 years]: aOR, 1.10; 95% CI, 1.06-1.14; P = .03) or income (<50th percentile: aOR, 1.17; 95% CI, 1.14-1.21 vs ≥50th percentile: aOR, 1.12; 95% CI, 1.09-1.16; P = .02) or who were exposed to limited green space (<50th percentile: aOR, 1.19; 95% CI, 1.15-1.23 vs ≥50th percentile: aOR, 1.12; 95% CI, 1.09-1.15; P = .003), more wildfire smoke (≥50th percentile: aOR, 1.19; 95% CI, 1.16-1.23 vs <50th percentile: aOR, 1.13; 95% CI, 1.09-1.16; P = .009), or extreme heat (aOR, 1.51; 95% CI, 1.42-1.59 vs mild temperature: aOR, 1.11; 95% CI, 1.09-1.14; P < .001). In this study, exposures to PM2.5 and specific PM2.5 constituents during pregnancy were associated with increased odds of sPTB. Socioeconomic status and other environmental exposures modified this association.

A VAR Framework of Exchange Rates, Interest Rates, and Inflation Through COVID-19 in Turkey: Empirical Evidence From Linear Cointegration and Causality Analysis

In this study, we investigate the impact of exchange rates and interest rates on inflation in Turkey using monthly data from January 2004 to July 2020 obtained from the Turkish Statistical Institute. Our vector autoregressive (VAR) model showed an evidence of stochastic behaviour among the series. The autoregressive distributed lag (ARDL) results showed a short-run and long-run covariate between exchange rates, interest rates and inflation. Specifically, the findings showed a short-run and long-run relationship between inflation, producer price index (PPI), and Turkish interbank offer rates (TIBOR). However, there was no connection between inflation and dollar exchange rates (DSR) and commercial banks’ interest rates (CBIR). The VAR Granger causality results revealed the variables to be exogenous except DSR, which displayed endogenous to other variables. Nevertheless, the results revealed unidirectional causality from the producer price index (PPI) to DSR and unidirectional causation from TIBOR to CBIR. It means an increase in production costs through raw materials importation led to devaluation of the Turkish lira. Similarly, TIBOR rates drive CBIR high, making domestic lending more expensive, which will inhibit loan provisions to the private sectors, which will result in an economic contraction and eventually high inflation. Our unit roots breakpoint results pointed to breaks in the dataset were between 2016-2019, reflecting the effects of the Fetullah Terrorist Organization (FETO) failed coup, the 2018 U.S. embargo, and an assumed fiscal dominance as the major and direct causes of economic instability and inflation. However, Covid-19 may have acted as a contributing factor since then. Thus, we recommend that the monetary authorities articulate policy to avoid the assumed fiscal dominance.

Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area

Abstract A monthly correlation between urban vegetation growth and potential evapotranspiration (PET) is needed for better knowledge of controlling water resources and organized irrigation processes. This study aims to explore their relationship within an urban area like Baghdad, using a linear regression model to derive a best-fit line drawn in a scatterplot on a monthly time scale. Based on two different monthly data sources: weather variables (e.g., air temperature, solar radiation, and relative humidity) and Sentinel-2 satellite imagery of 2 years, 2018 and 2021, this study presented the interannual variations of PET and normalized difference vegetation index (NDVI). The choice of these years has a significant feature of climatic differences, which are arid and semi-arid, respectively. PET values were estimated by the Truc method, while the areas of vegetation (represented by NDVI) were calculated using the Geographic Information Sensing program. The results show that the maximum PET in both years was found in the summer months (June and July) with mean values of about 8.8 mm/day, while their minimum mean values of about 1.5 mm/day occurred in winter months (January and December). From the spatial distribution of NDVI, it was found that at positive pixels when NDVI &gt;0.2, vegetation cover in March, April, and December 2018 had large areas with more than 200 km2 in 2018, while they were largest only in May 2021 with 197.8 km2. There was a linear correlation with slope (0.03) and intercept (= 1.8) and a strong correlation, R 2 = 0.72. The practical implications of the findings contribute to enhancing a solid scientific basis for improving agricultural water management, especially under dry conditions.

Spatial dynamics of inflation in India: an econometric analysis

ABSTRACT The study examines whether inflation convergence across various states in India exists after the adoption of the Inflation Targeting (IT) using monthly data during 2011M01-2021M12. Compared to pre-IT, the number of states shows a rise in convergence, while the median half-life period declines during the IT period. Concerning convergence, we find multiple convergence in both pre-IT and IT periods. However, the number of states following the national trend is much greater in IT than in the pre-IT period despite COVID-19. The present results help policymakers envisage the possibility of augmenting uniform monetary policy with region-specific inflation management measures.

Patient, financial and environmental impacts of a Medicines Optimisation in Care Homes (MOCH) service on polypharmacy following structured medication reviews

Abstract Introduction An NHS community trust was commissioned in February 2023 to deliver a MOCH service to about 15,000 care home residents across an Integrated Care System (ICS). Pharmacists in the MOCH service undertake Structured Medication Reviews (SMRs) to reduce inappropriate polypharmacy, working closely with care homes, General Practitioners (GPs) and community pharmacies. Pharmacy technicians undertake medication reviews to reduce low clinical value medicines. A patient-centred approach means medicines are stopped or changed following shared-decision making with the resident, carer or family. Aim To find out the impact of the MOCH service on reducing inappropriate polypharmacy, reducing medicines-related harm for residents, and to report financial savings and the environmental impact through reduction of CO2 emissions. Methods This service evaluation was approved by the Trust. No ethics approval was required. Quarterly and 6- monthly data sets covering one week reported by the MOCH service in the financial year 2023/2024 were used. These data sets were extrapolated to a full year. This service reported the number of medicines stopped, started and changed over one week of each quarter for SMRs and, pharmacy technicians reported every six months. Cost savings were calculated using the drug tariff based on continued use of medicines for one year. Pharmacists reported reduction in harm from medicines every six months based on a health interventions risk assessment scoring tool, assessing how many residents had potentially avoided moderate to serious harm following a SMR. The carbon savings were calculated based on financial savings from medicines stopped or changed using the DEFRA SIC 2020 Greenhouse Gases emission factor 0.621(kgCO2e/£) for pharmaceuticals1. Results In the first year the MOCH service completed SMRs for 11,363 residents (75% of care home residents in the ICS). Around 20,000 medicines for residents were stopped (one to two medicines per resident). Pharmacists predicted moderate to high-risk harm from medicines was reduced in approximately 4,200 residents. The cost savings from medicines stopped or changed was approximately £2.8 million, which translated to carbon savings of 1,773,340 kgCO2e, the equivalent of removing 644 cars from the road for one year. Discussion and Conclusion Reducing inappropriate polypharmacy resulted in a reduction of treatment burden, potential harm to residents2 and financial savings. Social impacts include reducing workload for care homes, GPs and community pharmacies, ultimately increasing the capacity of this stretched workforce (less dispensing, reduced risk of error, shorter medicine rounds and more time for residents). The environmental impact goes beyond carbon savings from pharmaceuticals to include reduction in workload, consumables, delivery and cost of waste disposal and prevention of hospital admissions.3 The limitations of this evaluation are that data collected over one week and then extrapolated may not be representative of all the other weeks in terms of cost savings and reduction of harm to residents, however MOCH pharmacists undertake peer reviews of reduction in harms to mitigate this. Costs incurred in making the financial savings were excluded. As the demographic of older people rises in the next 20 years a medication review is increasingly important to residents, the health economy, workforce, and our environment.

Systematic Upstream Large-Scale Control of Subtropical Low-Cloud Properties

Abstract It has recently been shown that the slow adjustment of the atmospheric boundary layer (ABL) to perturbations of the large-scale atmospheric conditions translate into an upstream control of the low-cloud cover (LCC) variability at climatological timescales in the subtropics. In this study we expand upon this recent study to investigate upstream control of the climatology of low-cloud radiative effect (CRE), as well as cloud properties relevant to their radiative effect: cloud liquid water path (LWP), and cloud optical depth (COD).We use machine-learning statistical models with feature selection capabilities (random-forests) to determine the influence of the local and upstream large-scale conditions in monthly data. These conditions are determined using back-trajectories in monthly-mean wind fields. Total CRE, dominated by the shortwave contribution, exhibits a dependence on upstream Estimated Inversion Strength (EIS), but not on upstream Sea-Surface Temperature (SST) as LCC does. Upstream control of COD was present but was not as consistent as LCC or CRE across different regions and cloud regimes, while LWP does not exhibit strong upstream control at all. This implies that the control of other boundary layer properties could explain the differences in response between LCC and CRE to SST and EIS. Looking at five subtropical eastern basins, it appears that key lead times are region-specific. The inclusion of upstream control provides significant improvements to the predictive skill of statistical models over local linear regression, with improvements in variance explained well over 20% in many cases.

Trade liberalization and total factor productivity in Brazil: A vecm modeling.

This paper aims to investigate trade openness's effects on total factor productivity (TFP) using monthly data from December 1991 to March 2024. The analysis also incorporated absorptive capacity to examine the behavior of TFP components. Our findings from a multivariate VECM model indicated that absorptive capacity did not significantly impact TFP, even in the short term. Conversely, the increase in openness contributes to raising TFP by about 26 and 0.16 percentage points in the short and long term, respectively. Additionally, absorptive capacity and trade openness Granger-Cause short- and long-term components of TFP. These results are statistically significant at conventional significance levels. Policymakers should consider the dynamic effects of their policy actions on other sectors of the economy that were not initially the focus of the policy. Policymakers should develop concrete policies that improve the efficient use of resources in production chains to potentialize the productive impact of trade liberalization, including investment in human capital, ICT, and research and development.

Spatiotemporal Evolution of Marine Heatwaves Globally

Abstract The spatiotemporal evolution of marine heatwaves (MHWs) is explored using a tracking algorithm called Ocetrac that provides objective characterization of MHW spatiotemporal evolution. Candidate MHW grid points are defined in detrended gridded sea temperature data using a seasonally varying temperature threshold. Identified MHW points are collected into spatially distinct objects using edge detection with weak sensitivity to edge detection and size percentile threshold criteria at each timestep. Ocetrac then uses 3D connectivity to determine if these objects are part of the same event, but Ocetrac only defines the full MHW event after all timesteps have been processed, limiting its use in predictability studies. Here Ocetrac is applied to monthly satellite sea surface temperature data from September 1981 through January 2021. The resulting MHWs are characterized by their intensity, duration, and total area covered. The global analysis shows that MHWs in the Gulf of Maine and Mediterranean Sea are spatially isolated, while major MHWs in the Pacific and Indian Oceans are connected in space and time. The largest and most long lasting MHW using this method lasts for 60 months from November 2013 to October 2018, encompassing previously identified MHW events including those in the Northeast Pacific (2014-2015), the Tasman Sea (2015-2016, 2017-2018), and the Great Barrier Reef (2016).

Exchange rate innovation, global pandemic and stock market returns: Empirical evidence from ECOWAS countries

This study used the panel VAR impulse response function model and high-frequency monthly data from 2020M1 to 2021M12 to examine the response of innovations in the exchange rate and stock market returns to the COVID-19 pandemic in Economic Communities of West African States (ECOWAS). The study found that the effect of shocks of COVID-19 today on future exchange rate innovation worsens the real conditions of exchange rate innovation in ECOWAS countries. Again, the impact of the shocks of COVID-19 today on future stock market returns encourages the real conditions of stock market returns in ECOWAS countries. It was recommended that instead of lockdown, ECOWAS governments should explore other policy options peculiar to the region in COVID-19 containment and also strive harder to deepen the stock market and encourage increased utilization of information and communication technology in stock market trading to cut costs, raise returns and connect trade with the rest of the world’s stock markets.

Causality relationships between climate policy uncertainty, renewable energy stocks, and oil prices: a mixed-frequency causality analysis

This paper investigates the predictive relationships among climate policy uncertainty (CPU), oil prices, and renewable energy (RE) stock market returns, particularly highlighting the challenges posed by the varying data frequencies of these variables. The study utilizes a comprehensive dataset comprising monthly CPU, daily oil prices, and RE stock returns, sourced globally. By applying a mixed-frequency causality test (MFCT), the analysis reveals significant predictability across different time horizons, particularly highlighting the strong influence of oil prices on RE stock returns over short-term horizons, while CPU demonstrates a more pronounced effect over medium to long-term horizons. In contrast, the application of the classical Granger causality test on low-frequency (monthly) data indicates an insignificant relationship between CPU and RE stocks, suggesting that traditional models may overlook important predictive dynamics. The analysis was conducted using Matlab code, and the findings provide valuable insights for policymakers in designing effective climate policies and for investors in optimizing portfolio strategies and hedging against risks.

The Effect of Food Price Stabilization on Inflation in West Nusa Tenggara 2019-2023

One of the primary contributors to the inflation rate in West Nusa Tenggara Province is the fluctuation of prices for food commodities. The objective of this study is to examine the extent to which fluctuations in food commodity prices, including those of rice, red chili, and shallots, contribute to inflationary trends in West Nusa Tenggara. The data used is monthly data on inflation and food commodity prices from 2019-2023 obtained from BPS (Central Bureau of Statistics), DKP (Food Security Agency), and the Agriculture Office of West Nusa Tenggara Province. The analysis method used is vector autoregression (VAR), which includes stationarity test, VAR stability test, optimal lag test, cointegration test, VAR estimation, impulse response function (IRF), and variance decomposition. The results of this study indicate that in the short term premium rice prices, curly red chili prices, and shallots do not affect inflation. Conversely, in the long run, the variable price of shallots does not affect inflation, while the variable price of premium rice and curly red chili prices exert an influence on inflationary pressures in West Nusa Tenggara Province. The Variance Decomposition Test indicates that the price of curly red chili contributes 37.24 percent to inflation in the fifth period, while premium rice has an effect of 8.66 percent on inflation in the second period and shallots have an effect of 7.93 percent on inflation in the fifth period.

The impact of external shocks on volatility persistence and market efficiency of the foreign exchange rate regime: evidence from Malawi

This study examines the nexus between external shocks and micro-transmission aspects of volatility persistence and market efficiency for the Malawian Foreign exchange market. Garch-type models are employed on monthly data stretching back to June 2011 through to October 2021. Results of the study show the presence of two structural breaks for the volatility series and one structural break for the return series that fall within the rolling window for external shock associated with the Russia-Ukrainian war. The negative nature of the shock leads to a significant additive impact on volatility persistence, asymmetry, and threshold at different levels of significance in the three models of Garch, E-Garch and T-Garch respectively. Relaxing the models confirms the presence of domestic influence. However, the external influence remains significant especially for the negative shock. As such, the leverage and volatility feedback effects of external shocks are corroborated. Augmenting the approach with a FRUH analysis reveals that the foreign exchange market does not follow a random walk as it departs from the 1:1 relationship between the spot and forward rate thus being weak-form inefficient.

Predicting Tourist Arrivals in Greece With a Novel Tourism-Specific Business Leading Indicator

We introduce a novel tourism-specific business expectations sentiment index and explore whether it can operate as a leading indicator for international tourist arrivals in Greece. Using monthly data spanning 2002‐2021 and employing a VAR model, we document that this newly introduced tourism-specific business expectations index serves as a leading indicator, whose higher levels foreshadow increased demand for international travel. We also find that its inclusion in a tourism-oriented model increases forecasting accuracy, which can be utilized by travel agent businesses, local government officials, and policymakers in their efforts to predict tourist arrivals in Greece.

Dynamics of HIV transmission among men who have sex with men in Taiwan: a mathematical modeling study

BackgroundIn Taiwan, the human immunodeficiency virus (HIV) is primarily transmitted among men who have sex with men (MSM). We believe that the primary source of heterogeneity influencing transmission is from whether the infected individuals engage in behaviors that promote transmission. Therefore, we differentiated and modeled the statuses of infected individuals, estimated parameters, and predicted future infection trends to better understand HIV transmission dynamics among MSM.MethodsWe devised a computational approach to accurately estimate the number of infectious individuals during early surveillance years in Taiwan using monthly data of newly diagnosed patients with HIV from January 2005 to December 2006. Subsequently, using annual incident cases from 2005 to 2019, we estimated the susceptibility rate, transmission rates, and duration of risk and conducted short-term forecasts of HIV infection among MSM through mathematical modeling based on the susceptible-infected-removed model. Parameters and their values, such as HIV and acquired immunodeficiency syndrome (AIDS) transmission rates and removal rates, were also estimated.ResultsA total of 850 infectious individuals with HIV were identified in 2005. From 2005 to 2019, approximately 0.68% (95% confidence interval: 0.64–0.71%) of Taiwan’s male population were estimated to be susceptible to HIV infection via MSM. The transmission rate did not significantly differ between individuals with HIV and AIDS (0.0110 and 0.107 per 10,000 individuals, respectively). The average infection duration between infection and AIDS onset was 4.5 years and between AIDS onset and death was 2.1 years. In 2019, the proportion of infectious infected individuals continuously decreased. By 2026, only 11.85% and 10.21% of individuals with HIV and AIDS, respectively, will be infectious.ConclusionsOur study presents a new dynamic mathematical model for estimating infectious HIV cases among MSM in Taiwan. By accounting for the heterogeneity of infectious HIV/AIDS within the MSM population, we effectively estimated the number of infections during early surveillance years and implement concentrated measures, thereby reducing infectious HIV/AIDS cases, which contributes to the overall reduction in HIV/AIDS cases. With these estimations, identifying target populations and implementing effective intervention measures at appropriate times can be improved.

Pengaruh Realisasi Pajak Kendaraan Bermotor, Bea Balik Nama Kendaraan Bermotor, Dan Retribusi Daerah Terhadap Pendapatan Asli Daerah Kota Bandar Lampung Tahun 2020-2023

This study aims to determine the effect of the Realization of Motor Vehicle Tax (PKB), Motor Vehicle Name Return Duty (BBNKB), and Regional Levy on Regional Original Revenue (PAD) of Bandar Lampung City. The independent variable contains PKB, BBNKB, and Regional Levy while the bound variable is PAD. This study uses a Quantitative Method by processing data. The sample in this study is the number of PKB, BBNKB and Regional Levy receipts from 2020 - 2023 (monthly data) as many as 48 samples. The analysis in this study is multiple linear regression analysis, classical assumption test, and hypothesis test with a significance level of 5%. From the results of the research that has been carried out, it shows that PKB, BBNKB and Regional Levy together (Simultaneous) have a significant effect of 86.4% while the remaining 23.6% are affected by other variables outside this study.

Asymmetric Effect of Oil Prices on Kazakhstan’s Stock Market Index and Exchange Rate

In this study, the asymmetric effect of oil prices in Kazakhstan on the exchange rate (USD/KZT) and Kazakhstan stock market index (KASE) returns was analyzed using the non-linear ARDL cointegration (NARDL) method with monthly data for the period January 2010-February 2024. As a result of the findings of the study, both positive and negative changes in oil prices statistically affect stock returns and exchange rates in the long term. The estimated long-term positive (0.115982) and negative (0.111234) coefficients of oil prices on KASE returns were found to be statistically significant at the 5% significance level. Thus, in the examined period, the KASE variable gave different reactions to positive or negative shocks in the oil price. In the model where the exchange rate is the dependent variable, the estimated long-term positive (-0.093875) and negative (-0.092918) coefficients of oil prices were found to be statistically significant at the 95% reliability level.

Monetary and Fiscal Policy Impacts on the Indian Sovereign Bond Market: A VAR Approach

This study analyses the dynamic relationship between yield curve behaviour and the macroeconomy in India, with a focus on both monetary and fiscal policy impacts. Using the monthly data on yields of Treasury bills and government securities from April 2000 to March 2020, we employ principal component analysis to extract the three yield curve factors—level, slope and curvature. We then use an unrestricted vector autoregressive model to analyse the relationship between these three yield curve factors and macroeconomic variables: inflation, GDP growth, exchange rate and monetary and fiscal policy indicators. Our findings reveal a bidirectional causality between yield curve factors and macroeconomic variables. Monetary policy plays an important role in shaping the yield curve, with short-term rates having more pronounced effects than long-term rates. Notably, this study is among the first to incorporate fiscal policy indicator in the Indian context, providing a more comprehensive understanding of policy impacts on the sovereign bond market. Our results offer valuable insights for policymakers and investors, showing the interrelationship of fiscal and monetary policies with bond market dynamics in emerging economies. This research contributes to the growing macrofinance literature and enhances our understanding of financial market dynamics in a developing economy. JEL Classification: E430, C32, G120, E44

Unveiling Extreme Dependencies between Oil Price Shocks and Inflation in Tunisia: Insights from a Copula Approach

We follow a non-linear dynamic correlation approach using a combination of a DCC-GARCH model and a copula model to capture the dependence between oil price changes and inflation in Tunisia. The case of Tunisia is particularly instructive since after having been an exporter and a major producer, it became a net oil importer in the 2000s. The study, based on monthly data spanning decades, selects a Gumbel copula and shows that beyond weak average dependencies, there is a strong correlation between extreme values, suggesting that inflation in Tunisia is more sensitive to extreme (positive) variations in oil prices than to average variations. The implications of these empirical results for economic policy are crucial for the Tunisian economy.Copyright© 2024 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.

Comprehensive evaluation of solar floating photovoltaic prospective in Saudi Arabia: Comparative experimental investigation and thermal performance analysis

Recently, floating photovoltaic systems have been regarded as a promising technology for producing clean energy by utilizing the surface of water bodies, such as lakes, rivers and oceans. This study introduces a comparative experimental study and energy performance evaluation of a 1.0 kW offshore floating photovoltaic (FPV) system and a nearby traditional ground-based PV system (GPV) installed in the eastern province of Saudi Arabia. The FPV system was deployed in the Arabian Gulf, 25 m off the coast, at an average depth of 1 to 1.5 m depending on tide, wave, and current intensity. The FPV system employs a strong novel eco-friendly platform structure made of recycled buoyant materials such as engineered plastic drums and wood. This system is anchored with tension cables and concrete blocks that can withstand the changing sea water conditions. The GPV system, on the other hand, was installed 150 m inland from the shore. Real-time monthly data monitoring and assessment indicated that FPV systems outperformed GPV systems in terms of lower PV panel surface temperatures, higher power output, and panel efficiency. Based on daily average back surface temperatures, FPV system temperature was decreased by 7.5 % to 21.34 % when compared to GPV. Moreover, the FPV system efficiency was also increased by 12.2 % when compared to the GPV system. This study aims to assist in promoting the applicability of solar floating photovoltaic systems to synergistically fulfill the requirements of sustainable electricity production for the arid costal community in Saudi Arabia and similar areas.