Vector Error Research Articles

Macroeconomic determinants of housing demand in Saudi Arabia: an autoregressive distributed lag approach

Purpose This study aims to investigate the macroeconomic factors influencing housing demand in Saudi Arabia using quarterly data for the period 2010 Q1–2024 Q2. Design/methodology/approach The autoregressive distributed lag bounds test and vector error correction model are used to determine the dynamic relationship between the macroeconomic factors. Findings The results reveal that the F-statistic value of 4.2043 is higher than the upper bound of the critical values at 5% level of significance, indicating long-run association among the series. While there is a negative and significant influence of interest and inflation rates on housing demand, income per capita and population have a positive and significant influence on housing demand. Similar result is found for the short run analysis except income per capita which has positive but insignificant impact. Moreso, the population seems to be very crucial to housing demand in both short-run and long-run periods. Social implications The outcome of the study has important policy implications by enjoining the policymakers in Saudi Arabia to consider a decisive management of monetary and fiscal policies to ensure that inflation and interest rates for housing are kept at a low level to encourage housing demand. Also, adequate policies should be put in place to ensure housing/property affordability that matches the increasing population due to tourism, urbanisation and growing birth rate. Originality/value Studies on the macroeconomic determinants of housing demand are less explored as most studies dwell more on social and demographic factors despite the importance of macroeconomic factors towards house ownerships. There is a dearth of related studies in Saudi Arabia.

The Effects of Exchange Rates Volatility and Inflation on Tanzania’s Trade Balance: Evidence from J-Curve Effect

All economies today are experiencing the volatility of exchange rates and inflation in global markets. Consequently, this affects the trade performance among trading partners globally. This study examines the effects of exchange rate volatility and inflation on Tanzania’s trade balance. Time series data spanning 1990 to 2020 were used from the World Bank and Bank of Tanzania (BOT). Moreover, J-Curve and Marshall Lerner's theories provided the theoretical arguments. Systematically, a Vector Error Correction Model (VECM) was employed for short- and long-run analysis. The findings reveal that, in the long run, inflation, Foreign Direct Investment, and Gross Domestic Product have a positive impact on the trade balance, while the Exchange Rate exerts a negative influence. In the short run, the exchange rate negatively affects Foreign Direct Investment, while Gross Domestic Product has a positive influence. Further, the gross domestic product also positively influences inflation. Furthermore, the exchange rate and gross domestic product significantly affect the trade balance negatively and positively respectively. Analysis of impulse response functions confirms the presence of the J-Curve effect, showing an initial deterioration in the trade balance following a depreciation of the domestic currency, which reverses after three periods. These findings suggest the need for effective exchange rate management, promotion of export competitiveness, and a good environment for foreign direct investment to enhance trade performance in Tanzania

Causality Relationship Between Producer and Consumer Price Indexes of Selected Meat Commodities in South Africa from 1991 to 2023

The South African meat industry plays an important role in food provision, income generation, and economic stability. However, inflation-driven volatility in commodity markets has intensified the focus on the nexus between producer and consumer price indexes, as significant meat price changes affect both producers and consumers. Therefore, this study explored the association and the causality between consumer price index (CPI) meat and producer price index (PPI) beef, mutton, pork, and chicken from 1991 to 2023 using the Vector Error Correction Model (VECM) and Granger causality test. The findings of the study revealed a short- and a long-run relationship among the variables with an adjustment speed (ECT) of 67.67%. No causal relationship was found between PPI beef and CPI meat, while unidirectional relationships were identified between CPI meat and PPI chicken, pork, and mutton. These results suggest that consumer meat prices impact production prices for chicken, pork, and mutton, but not for beef, indicating that beef price changes are influenced by factors other than general meat price fluctuations. Thus, while price controls or subsidies may manage price changes in chicken, pork, and mutton, further research or targeted strategies are needed to address the unique factors influencing beef prices. Ultimately, understanding these dynamics will enhance price stability in the meat market, benefiting consumers, producers, and the overall stability of the South African economy.

Socio-Demographic Determinants of Mortality in Bangladesh: A Time Series Analysis

Understanding the factors influencing the death rate in Bangladesh is essential for effective policy-making and addressing demographic challenges. This study aims to examine both the short-term dynamics and long-term equilibrium relationships between socio-demographic factors and the death rate of Bangladesh over a given period. It focuses on four key factors: adolescence fertility rate (AFR), life expectancy rate at birth, birth rate, and infant mortality rate (IMR). Taking an annual time series dataset from 1975 to 2021 from the World Bank (WB), the study uses the Johansen co-integration test, vector error correction model (VECM), and Granger causality test to analyze the relationships between these factors and death rate. The findings reveal short-term and long-term equilibrium links between the socio-demographic parameters and death rate. A substantial negative correlation exists between death rate and AFR and life expectancy. Additionally, a positive correlation is observed between the death rate and birth rate, and IMR. These findings provide valuable insights for decision-makers to address the death rate in Bangladesh, bridging a research gap and guiding effective socio-demographic policies. International Journal of Statistical Sciences, Vol. 24(2), November, 2024, pp 35-54

Impact of Public Transport Infrastructure Investment on Economic Growth in Nepal

This paper assesses the relationship between public transport infrastructure investment and economic growth in Nepal using time series data. The study uses Vector Error Correction Model (VECM) to study the short and long-run relationship between public transport infrastructure investment and economic growth in Nepal during the period from 1974-2019. The study finds that in the short run, there is an initial negative impact of public transport infrastructure investment on economic growth, which attenuates over time and eventually transitions to a positive effect. The study concludes that while challenges persist, strategic investments in public transport infrastructure remain a cornerstone for Nepal's journey towards sustained economic growth, prosperity, and inclusive growth.

Trade Globalization, Overseas Investment, and Tax Revenue Growth in Sub-Saharan Africa

Abstract The financial setbacks of the sub-Saharan African regions have necessitated this study. The study assesses the role of trade openness and foreign direct investment (FDI) in driving tax revenue growth in sub-Saharan Africa. The major parameter representing the dependent variable is tax revenue growth while the independent factors include trade openness, exports, imports, and GDP as a moderating element. The research runs from 1990 to 2022 and employs the vector error correction model (VECM), with a unit root test that yields order one, while the Johansen co-integration test shows a long-run connection for all variables. The VECM results suggest that the long-run disequilibrium is corrected at a positive rate of 8.5%. It is also noteworthy that a percentage change in trade openness would result in a 13.7% decrease in tax income, but fluctuations in all other parameters except GDP will enhance tax revenue growth in sub-Saharan Africa. The test for the impact of all criteria on tax revenue growth yields minor results; however, tax revenue growth initiatives in Sub-Saharan Africa have a negative short- term effect on FDI but a favourable long-term impact. In addition, trade openness has a negative effect on GDP and exports in the short run, while imports have a negative impact on foreign investment. The policy implications include that bilateral trade policies will need to be reviewed, with an emphasis on exports, economic growth, and tax collection schemes. In addition, the governments in sub-Saharan African regions are encouraged to enact tax policies that would engender the inflow of overseas investment.

FDI dan Emisi CO₂: Apakah Ada Hubungan Kausal di ASEAN? Studi Kasus Indonesia, Malaysia, dan Singapura

Economic growth is the main indicator for a country's economic health, where Foreign Direct Investment (FDI) plays an important role in boosting economic growth. ASEAN member countries, including Indonesia, Singapore, and Malaysia, have introduced various policies to facilitate FDI to encourage economic growth. This study aims to analyze the causal relationship between Foreign Direct Investment (FDI) and CO2 emissions in ASEAN, and vice versa, namely the relationship between CO2 emissions and FDI. The study was conducted in three ASEAN countries (Indonesia, Singapore, and Malaysia) with an analysis period from 1990 to 2022. The method used in this study is Vector Autoregression (VAR) followed by the Vector Error Correction Model (VECM). The results show that based on the Granger Causality Test, no causal relationship between FDI and CO2 emissions was found in the three countries studied. However, based on VECM analysis, it was found that the CO2 variable has an influence on FDI in Indonesia, Singapore, and Malaysia.

Generalized Estimating Equations for Survival Data With Dependent Censoring.

Independent censoring is usually assumed in survival data analysis. However, dependent censoring, where the survival time is dependent on the censoring time, is often seen in real data applications. In this project, we model the vector of survival time and censoring time marginally through semiparametric heteroscedastic accelerated failure time models and model their association by the vector of errors in the model. We show that this semiparametric model is identified, and the generalized estimating equation approach is extended to estimate the parameters in this model. It is shown that the estimators of the model parameters are consistent and asymptotically normal. Simulation studies are conducted to compare it with the estimation method under a parametric model. A real dataset from a prostate cancer study is used for illustration of the new proposed method.

Infrastructure Development And External Financing Nexus In Sub-Saharan Africa: Panel Vecm Analysis

Abstract Research background It is evident that relying solely on domestic financing cannot bridge the infrastructure gap in the Sub-Saharan African (SSA) region. Therefore, exploring alternative sources of financing becomes crucial to complement domestic efforts and address the infrastructure needs effectively. Purpose This study investigates the relationship between infrastructure development and external financing factors (foreign direct investment – FDI, private participation in infrastructure – PPI, and official development assistance – ODA) by considering the short- and long-run equilibrium and their causal direction. Research methodology These objectives are achieved by employing the panel vector error correction mechanism (PVECM), impulse response functions (IRF), variance decomposition analysis (VDCs), and VAR causality on a dataset covering 43 SSA countries from 2000 to 2021. Results The results reveal the presence of feedback causal relationships between infrastructure development and external financing factors, and PVECM results demonstrate that only private participation in infrastructure has a positive influence on infrastructure development both in the long and short-run, while ODA and FDI only influence infrastructure development in the long- run. Novelty The current study contributes to the existing literature by examining the impact of external financing factors on infrastructure development, with a specific focus on SSA, by considering the three major external financing factors (PPI, FDI, and ODA) as the determinants of infrastructure.

THE INFLUENCE OF MACROECONOMIC VARIABLES ON THE JAKARTA ISLAMIC INDEX (JII): AN ANALYSIS FROM 2010 TO 2023

Introduction: Sharia investment activities become one of the most promising economic activities. This is proven from the resilience of sharia capital market activities, which have remained strong despite the challenges of the Covid-19 pandemic. This research examine the influence of macroeconomic variables on the Jakarta Islamic Index (JII). Method: This research used a quantitative approach with time series data for the period of January 2010 to December 2023. Specifically, the Vector Error Correction Model (VECM) method was employed to examine both the long-term and short-term effects, as well as the shocks in macroeconomic variables on Jakarta Islamic Index (JII). Results: This study indicate that in the long term, the exchange rate, IHSG and WGP variables have a significant positive impact on JII, while the inflation variable has a significant negative impact. Conversely, the WGP variable shows an insignificant negative impact on stock movements rates within JII. In the short term, however, the variables of inflation, exchange rate, IHSG, COP (Crude Oil Prices) and WGP do not have any impact on the movement of shares listed on JII. Conclusions and Suggestions: The findings of this research encourage investors to pay more attention to the movement of macroeconomic rate variables and information from companies related to financial reports before making a decision to invest their capital. The inflation, exchange rate, and IHSG variables can be utilized as references in decision making because better movement of the IHSG and exchange rate and stable inflation are able to provide optimal returns for investors.

A Novel Direct-Binary Amplitude Modulator Integrated with a 16-Times Frequency Multiplier for 5G+ Applications

This article presents a novel passive direct binary amplitude modulator (AM) integrated with two frequency multipliers (FMs) and a drive amplifier. Both FMs are composed of a harmonic generator and a modified cascode buffer, along with an additional single-to-differential amplifier added in front of the first FM. The input frequency band (1.5–1.75 GHz) is up-converted to the intermediate frequency band of 4–5 GHz by the first FM, while the second FM up-converts the IF band to the target millimeter wave band of 24–28 GHz. Furthermore, the mm-wave amplitude is directly modulated by a capacitor ladder whose ratio is digitally programmable. This unique capacitor-ladder structure AM is employed to attain uniformly distributed constellation points and improve the output signal-to-noise ratio. The proposed modulator is fabricated on a 65-nm CMOS with a die size of 0.73 mm<sup>2</sup>. When applying the modulator to I/Q paths, 1.33% error vector magnitude for 256-QAM was measured at 26 GHz.

A Novel Algorithm for Precise Orbit Determination Using a Single Satellite Laser Ranging System Within a Single Arc for Space Surveillance and Tracking

A satellite laser ranging (SLR) system uses lasers to measure the range from ground stations to space objects with millimeter-level precision. Recent advances in SLR systems have increased their use in space surveillance and tracking (SST). The problem we are addressing, the precise orbit determination (POD) using one-dimensional range observations within a single arc, is challenging owing to infinite solutions because of limited observability. Therefore, general orbit determination algorithms struggle to achieve reasonable accuracy. The proposed algorithm redefines the cost value for orbit determination by leveraging residual tendencies in the POD process. The tendencies of residuals are quantified as R-squared values using Fourier series fitting to determine velocity vector information. The algorithm corrects velocity vector errors through the grid search method and least squares (LS) with a priori information. This approach corrects all six dimensions of the state vectors, comprising position and velocity vectors, utilizing only one dimension of the range observations. Simulations of three satellites using real data validate the algorithm. In all cases, the errors of the two-line element data (three-dimensional position error of 1 km and velocity error of 1 m/s, approximately) used as the initial values were reduced by tens of meters and the cm/s level, respectively. The algorithm outperformed the general POD algorithm using only the LS method, which does not effectively reduce errors. This study offers a more efficient and accurate orbit determination method, which improves the safety, cost efficiency, and effectiveness of space operations.

Vertical Market Integration Analysis of Rice in Indonesia

Rice is a staple food in Indonesia, but challenges in the country's rice markets and marketing systems persist, leading to significant losses for both producers and consumers due to volatile price fluctuations. The prices of various food products are rising sharply due to growing demand driven by population growth, which is not adequately supported by supply. This study aims to examine the vertical market integration of rice in Indonesia using the Vector Error Correction Model (VECM) as the analytical method. The findings reveal that the markets for harvested dry grain at the producer level and rice at the consumer level are integrated in the long term, indicating that changes in producer-level harvested dry grain prices are influenced by consumer-level rice prices. However, this integration is not observed in the short term.

CAUSALITY OF REGIONAL ORIGINAL INCOME (PAD), REGIONAL EXPENDITURE, POVERTY LEVEL AND ECONOMIC BENEFICTS

This study aims to determine the correlation between Regional Original Income (PAD), regional expenditures, poverty and economic benefits as measured by the level of the Human Development Index (IPM). This data research uses panel data from 23 districts/cities in Aceh in the period 2014-2019. Panel Vector Error Correction Model (PVECM) and panel Granger causality test were used to analyze the data. This study shows that there is a long-term relationship between variables, namely regional spending, poverty, and Human Development Index (IPM). Whereas in the shortterm PAD has no effect on poverty, but PAD does not affect regional spending and has a negative effect on HDI, then regional expenditure is not affected by poverty, but does not have a positive effect on HDI, while it has a negative impact on HDI. The results of the Granger Panel causality test can be found that there is a causal relationship between regional spending and HDI on PAD, while the disease has a one-way relationship with PAD. Then there is also a one-way relationship between regional spending and poverty on HDI, but poverty and HDI have no relationship between the two.

VECM MODEL IN MEASURING THE IMPACT OF MONETARY POLICY INTERVENTION ON ECONOMIC GROWTH IN INDONESIA FROM 2009 TO 2022

This research was conducted to determine the short-term and long-term effects of inflation, exchange rates, interest rates, and the money supply on economic growth in Indonesia from 2009 to 2022 using the Vector Error Correction Model (VECM) method. The VECM method is used to analyze the interaction between these variables over different time horizons, offering valuable insights into their respective roles in influencing economic growth. The results show that in the short run, the exchange rate variable does not have a significant effect on the economic growth, while in the long run the interest rate variable has a positive impact on the economy with a negative coefficient value. The short run variable interest rates do not have significant effects on the growth of the economy, but in the longer run interest rates have an important effect on growth. In conclusion, the effect of exchange rates on the Indonesian economy is still a controversial research topic. The findings enhance the current literature on macroeconomic policy and provide a foundation for policymakers to design more effective economic strategies, especially in addressing the challenges posed by inflation and exchange rate volatility in both the short and long terms.

A 32-channels analog multiplexer with crosstalk compensation technique in 45 nm CMOS

This paper presents a multiplexer that is capable of modulating 32-channels analog signal, which is a promising approach to simplify transmission system. An 8-channels prototype multiplexer with integral functionality and non-ideal factors is fabricated in 45 nm CMOS with area of 0.59 mm2, and verified in a QAM-256 system with 1.2V supply. The proposed multiplexer employs a semi-tree structure to achieve compromise between scale and speed. To relieve adverse effect caused by crosstalk between channels, the auxiliary reset compensation circuit combined with a dedicated timing sequence is utilized. Additionally, the proposed high-speed gate voltage bootstrap switch and high-bandwidth input buffer ensure that the signal remains linear during transmission. In the experimental result, the multiplexer can achieve a pulse width of at least 77ps in 8Gbps code rate, and the root mean square error due to nonlinearity between differential input and output is 1.869 %. The error vector magnitude (EVM) obtained by analyzing output versus input of multiplexer is less than 1.413 %.

Analysis of the Effect of Novel Coronavirus 2019 (Covid-19) Spreading Toward Sharia Stock Market in Indonesia

The purpose of this research is to identify and analyze the influence of the spread of Novel Coronavirus 2019 (Covid-19), the policies of Indonesian Government during pandemic (i.e. work from home, large-scale social restrictions (PSBB) and community activities restriction enforcement (PPKM), the movement of FTSE 100 and Nasdaq Composite indexes on Islamic stock market in Indonesia (represented by the Indonesian Sharia Stock Index). This study utilizes the Vector Error Correction Model (VECM), Impulse Response Function (IRF), and Forecast Error Correction Model (FEVD) approach, with the range data from September 2019 to November 2022. The results of this research indicates that the VECM test showed that Covid-19 case in Indonesia and the movement of FTSE 100 had a significant positive effect on ISSI in the long term. Meanwhile, in the short term, Covid-19 case in Indonesia and government policies have had a significant negative effect on ISSI. In the IRF test, this shows that the Covid-19 case in Indonesia and government policies during pandemic have had a significant negative effect on ISSI. Conversely, the movement of the FTSE 100 and Nasdaq Composite Index has a significant positive effect on ISSI. In the FEVD test, it can be seen that the biggest contribution to ISSI shock movement was the shock itself of 85.24% and was followed by government policies, the Covid-19 case, FTSE 100 and Nasdaq. This investigation use three variables in order to search the effect of these factors on the movement of sharia stock market in Indonesia. The stock market represented by Indonesian Sharia Stock Index (ISSI).

Analysis of The Influence of The Value of Non-Cash Payment Transactions on The Amount of Money Supply in Indonesia

This literature explains the influence of credit card, debit card, and e-money transaction values on Indonesia’s M1 and M2 money supplies. Time series data from January 2010 to August 2023 are used taken from the official websites of Bank Indonesia and the Central Statistics Agency . The Vector Error Correction Model (VECM) is the analysis method employed. According to the study’s findings, the M1 and M2 money supply is significantly impacted by the value of debit card transactions in both the short and long term. While it has a large short-term impact on M1 and M2, the credit card transaction value variable has a negligible long-term impact on M2. In addition, the value of e-money transactions demonstrates that they have a large impact on M1 both in the short and long terms. On the other hand, it has a significant impact on M2 in the short term but not on M2 in the long run.

EVM-Aware relay path decision with hierarchical modulation for reliable data transmission in cooperative relay networks

This paper presents a novel approach of integrating an error vector magnitude with hierarchical modulation in which HM dynamically adjusts modulation schemes to optimize spectral efficiency under varying channel conditions. Relay nodes are strategically selected based on Signal-to-Noise Ratio (SNR), with a focus on prioritizing high-SNR relays to ensure reliable data forwarding. To further enhance the reliability of the communication system, an EVM-aware relay path decision is proposed which selects the most suitable path based on EVM, considering the quality of the transmitted signal. By considering both SNR-based relay selection and EVM-aware path selection, the proposed system aims to minimize errors and optimize the overall performance of the network. The effectiveness of the proposed system is evaluated through extensive simulations in MATLAB, demonstrating that the proposed adaptive modulation scheme significantly outperforms fixed schemes, particularly under fluctuating channel conditions, ensuring robust and reliable communication across different SNR levels. This shows the potential of the proposed protocol to enhance performance in dynamic, making it particularly relevant for applications where reliable data transfer is critical.

What Drives the Profitability of Islamic Banks?: Insights from Indonesia Using the Vector Error Correction Model (VECM) Approach

This study examines the influence of various Islamic financing mechanisms – mudarabah, murabaha, musharakah, liquidity, and financing risk – on the profitability of Islamic banking institutions in Indonesia from 2011 to 2020. Utilizing a quantitative approach, the research aims to thoroughly assess both the short-term and long-term effects of these variables on the dependent variable, Islamic banks’ profitability. The analysis is based on panel data from the Indonesian Islamic banking sector during the specified period and employs the vector error correction model (VECM) method for data analysis. The outcomes of the estimation tests indicate that each of these variables significantly impacts the return on assets (ROA) of Islamic banks in Indonesia, both in the short and long term, throughout the given period. The findings reveal that changes in mudarabah, murabaha, musharakah, non-performing financing, and financing-to-deposit ratio have led to measurable responses in the ROA of these institutions. This study offers valuable insights into the relationship between Islamic financing components and the profitability of Islamic banks in Indonesia, contributing to a deeper understanding of the financial dynamics in this sector over the past decade. Keywords: Islamic banks, Islamic financing, profitability, VECM