scholarly journals Mutual information analysis of the factors influencing port throughput

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Majid Eskafi ◽  
Milad Kowsari ◽  
Ali Dastgheib ◽  
Gudmundur F. Ulfarsson ◽  
Poonam Taneja ◽  
...  
Keyword(s):  
Mutual Information ◽  
Epistemic Uncertainty ◽  
Fuel Oil ◽  
Throughput Analysis ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Port Throughput ◽  
Strong Relation ◽  
Marine Products ◽  
Measure Of Dependence

Purpose Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables. Design/methodology/approach Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable. Findings This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput. Originality/value Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.

Modeling of assembly systems with complex structures for throughput analysis during transients

2019 ◽  
Vol 39 (2) ◽  
pp. 262-271
Author(s):  
Yukan Hou ◽  
Yuan Li ◽  
Yuntian Ge ◽  
Jie Zhang ◽  
Shoushan Jiang
Keyword(s):  
Steady State ◽  
Fixed Point Theory ◽  
Point Theory ◽  
Assembly Systems ◽  
Complex Structures ◽  
Throughput Performance ◽  
Throughput Analysis ◽  
Content Type ◽  
Serial Production Lines ◽  
Transient And Steady State

Purpose The purpose of this paper is to present an analytical method for throughput analysis of assembly systems with complex structures during transients. Design/methodology/approach Among the existing studies on the performance evaluation of assembly systems, most focus on the system performance in steady state. Inspired by the transient analysis of serial production lines, the state transition matrix is derived considering the characteristics of merging structure in assembly systems. The system behavior during transients is described by an ergodic Markov chain, with the states being the occupancy of all buffers. The dynamic model for the throughput analysis is solved using the fixed-point theory. Findings This method can be used to predict and evaluate the throughput performance of assembly systems in both transient and steady state. By comparing the model calculation results with the simulation results, this method is proved to be accurate. Originality/value This proposed modeling method can depict the throughput performance of assembly systems in both transient and steady state, whereas most exiting methods can be used for only steady-state analysis. In addition, this method shows the potential for the analysis of complex structured assembly systems owing to the low computational complexity.

Macroeconomic fundamentals and dynamics of the Indian rupee-dollar exchange rate

2015 ◽  
Vol 7 (4) ◽  
pp. 301-326 ◽  
Author(s):  
Chandan Sharma ◽  
Rajat Setia
Keyword(s):  
Exchange Rate ◽  
Structural Break ◽  
Cointegration Analysis ◽  
Least Square ◽  
Dollar Exchange Rate ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Indian Rupee ◽  
Macroeconomic Fundamentals ◽  
The Impact

Purpose – This paper aims to examine the relationship between Indian rupee-US dollar exchange rate and the macroeconomic fundamentals for the post-economic reform period. Design/methodology/approach – The authors have used an empirical model which includes a range of important macroeconomic variables based on the basic monetary theories of exchange rate determination. At the first stage of the analysis, they have tested structural break in the data. Subsequently, they have employed the fully modified ordinary least square, Wald’s coefficient restriction and impulse response functions (IRF) to estimate the monetary model in the long- and short-run horizons. Findings – Results of analyses indicate that the macroeconomic fundamentals determine exchange rate in a significant way, but their effect varies sizably across the periods. The IRF illustrate the importance of interest rate in controlling exchange rate volatility. Practical implications – The analysis of the behavior of inter-relationship among macroeconomic variables will help policymakers in a deep-rooted understanding of this complex and time-varying relationship. Originality/value – Most of the existing studies have tested the impact of a single or a few macroeconomic fundamentals on exchange rate. But in the present study, we have tested the impact of a range of important variables, i.e. money supply, real income or output, price level and trade balance. Further, considering the importance of structural breaks in data, they authors have employed standard tests of structural break and incorporated the issue in the cointegration analysis.

Exploring the relationship between macroeconomic indicators and sovereign credit default swap in Pakistan

2017 ◽  
Vol 18 (4) ◽  
pp. 368-380
Author(s):  
Abdul Rashid ◽  
Farooq Ahmad ◽  
Ammara Yasmin
Keyword(s):  
Exchange Rate ◽  
Credit Default Swap ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Long Run ◽  
Credit Default ◽  
Macroeconomic Indicators ◽  
Short Run ◽  
The Exchange Rate ◽  
The Interest Rate

Purpose This paper aims to empirically examine the long- and short-run relationship between macroeconomic indicators (exchange rates, interest rates, exports, imports, foreign reserves and the rate of inflation) and sovereign credit default swap (SCDS) spreads for Pakistan. Design/methodology/approach The authors apply the autoregressive distributed lag (ARDL) model to explore the level relationship between the macroeconomic variables and SCDS spreads. The error correction model is estimated to examine the short-run effects of the underlying macroeconomic variables on SCDS spreads. Finally, the long-run estimates are obtained in the ARDL framework. The study uses monthly data covering the period January 2001-February 2015. Findings The results indicate that there is a significant long-run relationship between the macroeconomic indicators and SCDS spreads. The estimated long-run coefficients reveal that both the interest rate and foreign exchange reserves are significantly and negatively, whereas imports and the rate of inflation are positively related to SCDS spreads. Yet, the results suggest that the exchange rate and exports do not have any significant long-run impact on SCDS spreads. The findings regarding the short-run relationship indicate that the exchange rate, imports and the rate of inflation are positively, whereas the interest rate and exports are negatively related to SCDS spreads. Practical implications The results suggest that State Bank of Pakistan should design monetary and foreign exchange rate polices to minimize unwanted variations in the exchange rate to reduce SCDS spreads. The results also suggest that it is incumbent to Pakistan Government to improve the balance of payments to reduce SCDS spreads. The findings also suggest that the inflation targeting policy can also help in reducing SCDS spreads. Originality/value This is the first study to examine the empirical determinants of SCDS spreads for Pakistan. Second, it estimates the short- and long-run effects in the ARDL framework. Third, it considers both internal and external empirical determinants of SCDS spreads.

Long run apartment price dynamics in Swedish and German cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sviatlana Engerstam
Keyword(s):  
Banking Sector ◽  
Cointegration Analysis ◽  
Price Dynamics ◽  
Long Term Effects ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Price Elasticities ◽  
Long Run ◽  
German Cities

PurposeThis study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.Design/methodology/approachThe main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.FindingsThe empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.Originality/valueIn distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.

Market overreaction, firm-specific information and macroeconomic variables in US and Chinese markets during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ooi Kok Loang ◽  
Zamri Ahmad
Keyword(s):  
Unemployment Rate ◽  
Stock Return ◽  
Design Methodology ◽  
Specific Information ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Real Gdp ◽  
Chinese Markets ◽  
The Impact ◽  
Loser Portfolio

PurposeThis study examines the impact of firm-specific information and macroeconomic variables on market overreaction of US and Chinese winner and loser portfolio before and during COVID-19.Design/methodology/approachThe firm-specific information includes firm size, volume, volatility, return of asset (ROA), return of equity (ROE), earning per share (EPS) and quick ratio while the macroeconomic variables are export rate, import rate, real GDP, nominal GDP, FDI, IPI and unemployment rate. Besides, one-third of the top performance stocks are categorized as winner portfolio while one-third of lowest performance stocks are categorized as loser portfolio. This study uses AECR to indicate stock return and measure market overreaction. GAECR is used to determine contrarian profit. The data range of pre-COVID-19 is from 1-Jan-2015 to 31-Dec-2019 while the period of COVID-19 is from 1-Jan-2020 to 31-Dec-2020.FindingsIn pre-COVID-19, firm-specific information (volatility, ROA, ROE and EPS) and macroeconomic variables are found to be correlated to stock return in US and Chinese portfolios except Chinese winner portfolio. Nonetheless, the impact of firm-specific information has vanished and macroeconomic variables are significant to stock return in COVID-19. It shows that investors rely on the economic indicators to trade in turbulent period due to emergence of COVID-19 as a disruption in market. Furthermore, US and Chinese portfolios are overreacted during COVID-19. Chinese loser portfolio has higher tendency of overreaction than US loser portfolio while US winner portfolio has higher tendency of overreaction than Chinese winner portfolio.Originality/valueThe results of this study assists academician, practitioners and investors on understanding and create awareness to the existence of market overreaction and the determinants that can cause the phenomenon.

Are mom-and-pop and professional hosts actually competing against hotels?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruggero Sainaghi ◽  
Rodolfo Baggio
Keyword(s):  
Mutual Information ◽  
Design Methodology ◽  
Management Policy ◽  
Seasonal Patterns ◽  
Content Type ◽  
Rhythmic Behavior ◽  
Direct Competition ◽  
Information Metric ◽  
Fierce Competition ◽  
Practical Implications

Purpose This paper aims to examine the question of whether commercial, peer-to-peer accommodation platforms (Airbnb, in particular) and hotels are in fierce competition with each other with the possible presence of substitution threats, and compares the time series of the occupancy values across two supplier types. Design/methodology/approach The cities of Milan and Rome are used as case studies for this analysis. To assess the extent of synchronization, the series of Airbnb and hotels are transformed into a series of symbols that render their rhythmic behavior, and a mutual information metric is used to measure the effect. Findings The results show that Airbnb hosts and hotels have different seasonal patterns. The diverse occupancy trends support the absence of direct competition between Airbnb and hotels. The findings are consistent in the two analyzed cities (Milan and Rome). Interestingly, there are higher similarities between seasonal occupancy series of Airbnb listings in Milan and Rome, on one side, and hotels in Milan and Rome, on the other, than between Airbnb and hotels in the same city. Research limitations/implications The findings show a progressive de-synchronization (within mutual information) among the five groups of Airbnb hosts triggered by the rising professionalization degree. This result suggests the existence of a partial different business model for multi-listing hosts. Practical implications The study illustrates an absence of any substitution threat between Airbnb and hotels in both cities. This could have important consequences, especially for the pricing and revenue management policy. In fact, the higher the substitution threat, the higher the attention that Airbnb entrepreneurs should pay to the pricing strategy implemented by hotels, and vice versa. Originality/value This study sheds new light on the competition threat between Airbnb and hotels. In this study, hotels and Airbnb hosts appear as two very separate markets.

The macroeconomic effects of increase and decrease in oil prices: evidences of asymmetric effects from India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anver Chittangadan Sadath ◽  
Rajesh Herolli Acharya
Keyword(s):  
Negative Impact ◽  
Wholesale Price ◽  
Oil Prices ◽  
Petroleum Products ◽  
Oil Price ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Real Gdp ◽  
Oil Price Shock ◽  
Price Shock

Purpose The purpose of this paper is to assess whether oil price shocks emanating from oil price increase and decrease have a different impact on the macroeconomic activity. Design/methodology/approach This study conducts the empirical analysis using structural vector auto-regressive model on Indian data for the period from 1996 to 2017. This paper uses four key macroeconomic variables, namely, real gross domestic product (GDP), the real rate of interest, real money supply, wholesale price index inflation and various linear and non-linear measures of oil price shock. Findings Empirical results confirm that oil price shock has a significant impact on various macroeconomic variables used in the study. Specifically, shocks emanating from a decline in oil price have a stronger positive impact on real GDP, whereas, a shock due to the rise in oil price has a weaker negative impact on real GDP. Impulse responses confirm that shocks due to a decline in oil prices are long-lasting compared to similar shocks due to a rise in oil prices. Therefore, this study concludes that the macroeconomic impact of oil price shock is asymmetric in India. Originality/value This paper adds the following new insights: First, this paper presents a distinct relationship between the growth rate of oil price and GDP during increasing and decreasing phases of oil price to drive home the case for this study. Second, India has adopted crucial administrative initiatives such as deregulation of the market for petroleum products and the promotion of renewable energy during the study period. Finally, previous studies have revealed specific behavioral and economic features of people in India with respect to the demand for petroleum products. In light of these factors, this paper based on Indian experience would be justified.

Matching Attributes across Overlapping Heterogeneous Data Sources Using Mutual Information

2012 ◽  
pp. 417-437
Author(s):  
Huimin Zhao
Keyword(s):  
Mutual Information ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Heterogeneous Data Sources ◽  
Attribute Matching ◽  
Measure Of Dependence

Identifying matching attributes across heterogeneous data sources is a critical and time-consuming step in integrating the data sources. In this paper, the author proposes a method for matching the most frequently encountered types of attributes across overlapping heterogeneous data sources. The author uses mutual information as a unified measure of dependence on various types of attributes. An example is used to demonstrate the utility of the proposed method, which is useful in developing practical attribute matching tools.

Does macroeconomic uncertainty really matter in predicting stock market behavior? A comparative study on China and USA

2020 ◽  
Vol 10 (4) ◽  
pp. 393-427 ◽  
Author(s):  
Ghulam Abbas ◽  
Shouyang Wang
Keyword(s):  
Risk Factors ◽  
Financial Crisis ◽  
Stock Market ◽  
Global Financial Crisis ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Macroeconomic Risk ◽  
Stock Market Return ◽  
Macroeconomic Uncertainty ◽  
The Impact

PurposeThe study aims to analyze the interaction between macroeconomic uncertainty and stock market return and volatility for China and USA and tries to draw some invaluable inferences for the investors, portfolio managers and policy analysts.Design/methodology/approachEmpirically the study uses GARCH family models to capture the time-varying volatility of stock market and macroeconomic risk factors by using monthly data ranging from 1995:M7 to 2018:M6. Then, these volatility series are further used in the multivariate VAR model to analyze the feedback interaction between stock market and macroeconomic risk factors for China and USA. The study also incorporates the impact of Asian financial crisis of 1997–1998 and the global financial crisis of 2007–2008 by using dummy variables in the GARCH model analysis.FindingsThe empirical results of GARCH models indicate volatility persistence in the stock markets and the macroeconomic variables of both countries. The study finds relatively weak and inconsistent unidirectional causality for China mainly running from the stock market to the macroeconomic variables; however, the volatility spillover transmission reciprocates when the impact of Asian financial crisis and Global financial crisis is incorporated. For USA, the contemporaneous relationship between stock market and macroeconomic risk factors is quite strong and bidirectional both at first and second moment level.Originality/valueThis study investigates the interaction between stock market and macroeconomic uncertainty for China and USA. The researchers believe that none of the prior studies has made such rigorous comparison of two of the big and diverse economies (China and USA) which are quite contrasting in terms of political, economic and social background. Therefore, this study also tries to test the presumed conception that macroeconomic uncertainty in China may have different impact on the stock market return and volatility than in USA.

scholarly journals The relationship between debt and a firm’s performance: the impact of institutional factors

2019 ◽  
Vol 45 (9) ◽  
pp. 1272-1291 ◽  
Author(s):  
Rosa Forte ◽  
José Miguel Tavares
Keyword(s):  
Fixed Effects ◽  
Negative Relationship ◽  
Research Area ◽  
Institutional Framework ◽  
Market Regulation ◽  
Fixed Effects Model ◽  
Content Type ◽  
Macroeconomic Variables ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to contribute to the existing literature on the relationship between debt and firms’ performance, by focusing on the influence of the institutional framework on this relationship and on the role of macroeconomic variables in explaining performance. Design/methodology/approach The present work is based on a large sample of 48,840 manufacturing firms from nine European countries covering the 2008–2013 period and uses a fixed effects model. Findings Results show that the impact of debt on a firm’s performance depends on the measure of debt (short-term debt positively affects a firm’s performance, whereas long-term debt presents a negative relationship) and that the institutional framework is indeed affecting the relationship between debt and a firm’s performance: the positive effect of debt on a firm’s performance tends to be higher the greater the “efficiency of the legal system” and the greater the “credit market regulation.” Macroeconomic variables also play a key role in explaining performance. Originality/value Unlike most of the existing studies, which focus only on the relationship between debt and firms’ performance in a single country, the present work uses a sample of firms from nine countries with the purpose of filling a research gap and bringing new empirical evidence to this research area.

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