Analysis of Lumber and Pulpwood Production in a Partial Adjustment Model with Dynamic and Variable Speeds of Adjustment

1986 ◽  
Vol 4 (3) ◽  
pp. 305 ◽  
Author(s):  
Winston T. Lin
Keyword(s):  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model

A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector

2009 ◽  
Author(s):  
Anthony C. Paul ◽  
Erica C. Myers ◽  
Karen L. Palmer
Keyword(s):  
Electricity Demand ◽  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model

scholarly journals PENGARUH LIBERALISASI ARUS MODAL TERHADAP PERTUMBUHAN EKONOMI ASEAN-5

2020 ◽  
Vol 3 (2) ◽  
pp. 345-354
Author(s):  
Devilia Sitorus ◽  
Crisanty Sutristyaningtyas Titik
Keyword(s):  
Economic Growth ◽  
Significant Influence ◽  
Capital Flows ◽  
The Philippines ◽  
Financial Openness ◽  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model ◽  
Short And Long Term

This study aims to examine the relationship between capital flow liberalization and economic growth in ASEAN-5. This research is a quantitative study that uses data: GDP, Gross Capital Formation, financial disclosure seen from the Chinn-Ito index for the period 2000-2017 in 5 ASEAN countries namely Indonesia, Malaysia, the Philippines, Singapore, and Thailand. Data were processed using panel data regression analysis and specifically for Indonesia, Partial Adjustment Model (PAM) regression was performed. The results of this study indicate that financial openness seen from the Chinn-Ito index has a negative and significant influence on the economic growth of ASEAN-5 countries. Capital flows have a positive and significant impact on the economic growth of ASEAN-5 countries. Meanwhile, the PAM (Partial Adjustment Model) regression model shows that capital flows have a positive and significant influence on Indonesia's economic growth both in the short and long term, while financial openness has a negative and significant impact on Indonesia's economic growth both in the short and long term.

scholarly journals Comparison of Determinants of Capital Structure in Lippo Group and Bakrie Group Companies Listed on the Indonesia Stock Exchange (Partial Adjustment Model Approach)

2021 ◽  
Vol 8 (2) ◽  
pp. 83-88
Author(s):  
Fildzah Fitria ◽  
Khaira Amalia Fachrudin ◽  
Amlys Syahputra Silalahi
Keyword(s):  
Capital Structure ◽  
Stock Exchange ◽  
Company Size ◽  
Group Company ◽  
Partial Adjustment ◽  
Insignificant Effect ◽  
Adjustment Model ◽  
Growth Opportunity ◽  
Partial Adjustment Model ◽  
Model Approach

This study aims to determine the determinants of the capital structure of the Lippo Group and the Bakrie Group listed on the Indonesia Stock Exchange using the partial adjustment model approach. The population in the Lippo Group company is 12 and the population at the Bakrie Group company is 9. The sample of this study is that all companies listed on the Indonesia Stock Exchange are 21 companies. Data analysis used panel data regression method with partial adjustment model approach. The results of the research in the t test at the Lippo Group company show that the lag leverage has a positive and insignificant effect on leverage, profitability has a positive and significant effect on leverage, company size has a positive and insignificant effect on leverage, earning volatility has a positive and significant effect on leverage, assets tangibility has a positive and significant effect on leverage and growth opportunity has a positive and insignificant effect on leverage. The results of the research in the t test at the Bakrie Group company show that the lag leverage has a positive and insignificant effect on leverage, profitability has a positive and insignificant effect on leverage, company size has a positive and insignificant effect on leverage, earning volatility has a positive and insignificant effect on leverage, assets tangibility has a negative and insignificant effect on leverage, growth opportunity has a negative and insignificant effect on leverage. The partial adjustment model test results show that only Lippo Group company on the variables of profitability, earning volatility and assets tangibility have a significant positive effect on leverage. The results of the comparison of the optimal capital structure show that the Bakrie Group has a higher level of optimal capital structure by 83% than the Lippo Group at 55%. Keywords: Lag Leverage, Profitability, Company Size, Earning Volatility, Assets Tangibility, Growth Opportunity, Leverage.

Speed of adjustment and estimation of the partial adjustment model

1996 ◽  
Vol 3 (1) ◽  
pp. 21-23 ◽  
Author(s):  
Marcus J. Chambers
Keyword(s):  
Partial Adjustment ◽  
Speed Of Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model

Examining the Japanese seaweed market before and after the earthquake using a partial adjustment model of LA-AIDS

2016 ◽  
Vol 82 (3) ◽  
pp. 549-559 ◽  
Author(s):  
Hiroki Wakamatsu ◽  
Tsutomu Miyata
Keyword(s):  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model ◽  
Before And After

Carryover Effects and Temporal Aggregation in a Partial Adjustment Model Framework

1983 ◽  
Vol 2 (3) ◽  
pp. 297-317 ◽  
Author(s):  
Wilfried R. Vanhonacker
Keyword(s):  
Temporal Aggregation ◽  
Model Framework ◽  
Carryover Effects ◽  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model

scholarly journals Do Farmers Hedge Optimally or by Habit? A Bayesian Partial-Adjustment Model of Farmer Hedging

2010 ◽  
Vol 42 (4) ◽  
pp. 791-803 ◽  
Author(s):  
Jeffrey H. Dorfman ◽  
Berna Karali
Keyword(s):  
Risk Management ◽  
Panel Data ◽  
Information Sources ◽  
Aggregation Bias ◽  
Large Role ◽  
Management Decisions ◽  
Partial Adjustment ◽  
Adjustment Model ◽  
Partial Adjustment Model

Hedging is one of the most important risk management decisions that farmers make and has a potentially large role in the level of profit eventually earned from farming. Using panel data from a survey of Georgia farmers that recorded their hedging decisions for 4 years on four crops, we examine the role of habit, demographics, farm characteristics, and information sources on the hedging decisions made by 57 different farmers. We find that the role of habit varies widely and that estimation of a single habit effect suffers from aggregation bias. Thus, modeling farmer-level heterogeneity in the examination of habit and hedging is crucial.

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