scholarly journals Estimating a global demand model for soybean traffic through the Panama Canal

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Javier Ho ◽  
Paul Bernal
Keyword(s):  
Pacific Northwest ◽  
Least Square ◽  
Panama Canal ◽  
Demand Model ◽  
Department Of Agriculture ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Global Demand ◽  
Alternative Routes ◽  
The U.S

AbstractThis study attempts to fit a global demand model for soybean traffic through the Panama Canal using Ordinary Least Square. Most of the soybean cargo through the interoceanic waterway is loaded on the U.S. Gulf and East Coast ports -mainly destined to East Asia, especially China-, and represented about 34% of total Panama Canal grain traffic between fiscal years 2010–19. To estimate the global demand model for soybean traffic, we are considering explanatory variables such as effective toll rates through the Panama Canal, U.S. Gulf- Asia and U.S. Pacific Northwest- Asia freight rates, Baltic Dry Index, bunker costs, soybean export inspections from the U.S. Gulf and Pacific Northwest, U.S. Gulf soybean basis levels, Brazil’s soybean exports and average U.S. dollar index. As part of the research, we are pursuing the estimation of the toll rate elasticity of vessels transporting soybeans via the Panama Canal. Data come mostly from several U.S. Department of Agriculture sources, Brazil’s Secretariat of Foreign Trade (SECEX) and from Panama Canal transit information. Finally, after estimation of the global demand model for soybean traffic, we will discuss the implications for future soybean traffic through the waterway, evaluating alternative routes and sources for this trade.

Identification of Resistance to Powdery Mildew in Publicly Available Male Hop Germplasm

2018 ◽  
Vol 19 (3) ◽  
pp. 258-264
Author(s):  
David H. Gent ◽  
Briana J. Claassen ◽  
Megan C. Twomey ◽  
Sierra N. Wolfenbarger
Keyword(s):  
United States ◽  
Powdery Mildew ◽  
Pacific Northwest ◽  
Western United States ◽  
R Genes ◽  
Sources Of Resistance ◽  
Department Of Agriculture ◽  
Breeding Programs ◽  
The Pacific ◽  
The U.S

Powdery mildew (caused by Podosphaera macularis) is one of the most important diseases of hop in the western United States. Strains of the fungus virulent on cultivars possessing the resistance factor termed R6 and the cultivar Cascade have become widespread in the Pacific Northwestern United States, the primary hop producing region in the country, rendering most cultivars grown susceptible to the disease at some level. In an effort to identify potential sources of resistance in extant germplasm, 136 male accessions of hop contained in the U.S. Department of Agriculture collection were screened under controlled conditions. Iterative inoculations with three isolates of P. macularis with varying race identified 23 (16.9%) accessions with apparent resistance to all known races of the pathogen present in the Pacific Northwest. Of the 23 accessions, 12 were resistant when inoculated with three additional isolates obtained from Europe that possess novel virulences. The nature of resistance in these individuals is unclear but does not appear to be based on known R genes. Identification of possible novel sources of resistance to powdery mildew will be useful to hop breeding programs in the western United States and elsewhere.

scholarly journals The Factors Affecting Land Prices In Housing Location In Sidoarjo Regency

2017 ◽  
Vol 1 (1) ◽  
pp. 37-47
Author(s):  
Partomi Simangunsong ◽  
Arasy Alimudin ◽  
Muh. Barid Nizaruddin Wajdi
Keyword(s):  
Residential Location ◽  
Least Square ◽  
City Center ◽  
Sale Price ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Road Width ◽  
Log Linear ◽  
Road Distance

The need for residential location is one of the basic needs of the community and the attractiveness of the residential location is a unique feature where this feature is not made by the respective occupants, but by external factors from the residential environment in the area. This study aims to analyze the factors that are considered as the basis that affect the price of land. This research uses quantitative approach with associative research method. Linear analysis with quadratic method. Ordinary Least Square (OLS). From the analysis of this research model obtained log-linear F-accounting 70,162 while the value of F-table (0,05; 5,48) is 2,45. because F-count> F-table, Ho means rejected and explanatory variables include Distance to city center, Distance to main road, Distance to toll gate, Road width, and security simultaneously can be explained significantly at land sale price.

scholarly journals Determinants of Household Debt in Malaysia from the year 2010 to 2017

2019 ◽  
Vol 5 (2) ◽  
pp. 91
Author(s):  
Zahariah Mohd Zain ◽  
Nurul Ainun Ahmad Atory Ahmad Atory ◽  
Sarah Amirah Hanafi
Keyword(s):  
Positive Relationship ◽  
Negative Relationship ◽  
Housing Price ◽  
Least Square ◽  
Household Debt ◽  
Macroeconomic Variables ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Lending Rate

Household debt has become an issue in the Malaysian economy as it affects the country socially and economically.This study aims to examine the determinants of household debt from the year 2010 until 2017. This study employs the Ordinary Least Square (OLS) method and the macroeconomic variables used in this study are Gross Domestic Product (GDP), base lending rate, unemployment and housing price as independent variables. The results indicate that the trend of household debt in Malaysia has shown a continuous rise from the year 2010 to 2017. GDP, base lending rate and housing price indicate a positive relationship towards household debt while unemployment shows a negative relationship to household debt in Malaysia. All explanatory variables have shown a significant relationship except for GDP. Housing price has been found to be the most significant factor and positively related to household debt. The findings indicate that the higher the price of houses, the higher the household debt will be.

scholarly journals Third-Country Effects on the Market Shares of U.S. Wheat in Asian Countries

2004 ◽  
Vol 36 (3) ◽  
pp. 797-813 ◽  
Author(s):  
Hyun J. Jin ◽  
Guedae Cho ◽  
Won W. Koo
Keyword(s):  
Exchange Rates ◽  
Import Demand ◽  
Demand Model ◽  
Asian Countries ◽  
Panel Estimation ◽  
Explanatory Variables ◽  
Market Shares ◽  
Australian Wheat ◽  
The U.S ◽  
Country Effect

An import demand model, augmented with third-country effect variables, is developed to examine the effects of strong U.S. dollar, volatility of the U.S. dollar, and competition among the exporting countries on the shares of U.S. wheat in Asian markets. In the empirical model, the dependent variable is the market shares of U.S. wheat. Explanatory variables include wheat prices of exporting countries, exchange rates between the importing and exporting countries, and volatilities of the exchange rates. Panel estimation results show that the U.S. currency value and volatility, Australian wheat price, and the volatilities of Canadian and Australian currency values have significant effects on U.S. market shares.

scholarly journals A Data-Driven Approach to Trip Generation Modeling for Urban Residents and Non-local Travelers

2020 ◽  
Vol 12 (18) ◽  
pp. 7688
Author(s):  
Fan Yang ◽  
Linchao Li ◽  
Fan Ding ◽  
Huachun Tan ◽  
Bin Ran
Keyword(s):  
Cellular Phone ◽  
Test Methods ◽  
Least Square ◽  
Data Driven ◽  
Urban Residents ◽  
Trip Generation ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Data Driven Approach ◽  
Non Local

Trip generation modeling is essential in transportation planning activities. Previous modeling methods that depend on traditional data collection methods are inefficient and expensive. This paper proposed a novel data-driven trip generation modeling method for urban residents and non-local travelers utilizing location-based social network (LBSN) data and cellular phone data and conducted a case study in Nanjing, China. First, the point of interest (POI) data of the LBSN were classified into various categories by the service type, then, four features of each category including the number of users, number of POIs, number of check-ins, and number of photos were aggregated by traffic analysis zones to be used as explanatory variables for the trip generation models. We used a random tree regression method to select the most important features as the model inputs, and the trip models were established based on the ordinary least square model. Then, an exploratory approach was used to test the performance of each combination of the variables with various test methods to identify the best model for residents’ and travelers’ trip generation functions. The results suggest land use compositions have significant impact on trip generations, and the trip generation patterns are different between urban residents and non-local travelers.

scholarly journals Solving Multicollinearity Problem in Linear Regression Model: The Review Suggests New Idea of Partitioning and Extraction of the Explanatory Variables

2021 ◽  
Vol 2 (1) ◽  
pp. 12-20
Author(s):  
Kayode Ayinde, Olusegun O. Alabi ◽  
Ugochinyere Ihuoma Nwosu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Real Data ◽  
Least Square ◽  
Model Parameters ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Wide Range ◽  
High Level

Multicollinearity has remained a major problem in regression analysis and should be sustainably addressed. Problems associated with multicollinearity are worse when it occurs at high level among regressors. This review revealed that studies on the subject have focused on developing estimators regardless of effect of differences in levels of multicollinearity among regressors. Studies have considered single-estimator and combined-estimator approaches without sustainable solution to multicollinearity problems. The possible influence of partitioning the regressors according to multicollinearity levels and extracting from each group to develop estimators that will estimate the parameters of a linear regression model when multicollinearity occurs is a new econometrics idea and therefore requires attention. The results of new studies should be compared with existing methods namely principal components estimator, partial least squares estimator, ridge regression estimator and the ordinary least square estimators using wide range of criteria by ranking their performances at each level of multicollinearity parameter and sample size. Based on a recent clue in literature, it is possible to develop innovative estimator that will sustainably solve the problem of multicollinearity through partitioning and extraction of explanatory variables approaches and identify situations where the innovative estimator will produce most efficient result of the model parameters. The new estimator should be applied to real data and popularized for use.

scholarly journals The Effect of Foreign Direct Investment on the Unemployment Rate in Saudi Arabia

2020 ◽  
Vol 12 (10) ◽  
pp. 1
Author(s):  
Kolthoom Alkofahi
Keyword(s):  
Saudi Arabia ◽  
Foreign Direct Investment ◽  
Unemployment Rate ◽  
Direct Investment ◽  
Least Square ◽  
Total Output ◽  
Kingdom Of Saudi Arabia ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Job Opportunities

A substantial number of recent studies were devoted to investigating the effects of Foreign direct investment (FDI) on different economic variables. Although the connection between growth and investments is widely acknowledged, the connection between FDI and the unemployment rate is not easy to determine. Taking into consideration the dispute over the true effect of FDI on the host country’s economic performance, the study’s main purpose is to take advantage of the dispute and study the effect of foreign direct investment (FDI) on the unemployment rate (U) in the Kingdom of Saudi Arabia (KSA). Using Ordinary Least Square Model (OLS), the study takes the unemployment rate as a dependent variable, and FDI and Output as two explanatory variables over the period of 2005-2018. The study supports our assumption that the inflows of the FDI and the total output negatively and significantly affect the unemployment rate in the KSA; the inflows of the FDI creates more job opportunities and will reduce the unemployment rate in KSA. Our recommendation is that the KSA government should implement more policies to attract more inflows of “Quality FDI” to attain the maximum goals and to decrease the total unemployment rate.

ANALISIS UNDERGROUND ECONOMY INDONESIA DAN POTENSI PENERIMAAN PAJAK DI ERA TAX AMNESTY

INFO ARTHA ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 60-78
Author(s):  
Andi Wawan Mulyawan
Keyword(s):  
Time Series ◽  
Underground Economy ◽  
Least Square ◽  
Demand Model ◽  
Quarterly Data ◽  
Ordinary Least Square ◽  
Tax Amnesty ◽  
Currency Demand ◽  
Tax Loss ◽  
Data Period

The growth of underground economy activity believed has potential tax loss. This study aims to estimate the size of underground economy activities in Indonesia. Based on the results of these estimates, further calculated the potential tax loss due to the existence of underground economy activities. This study was conducted using quantitative approaches, namely currency demand model by Vito Tanzi (1980) and Faal (2003) which is estimated by ordinary least square (OLS) method. By using time series (quarterly) data period 2011-2015 this study found that the size o f underground economy is about Rp 536 trillion per year on average, equivalent to 22,1% of GDP. Meanwhile, the potential tax loss due to the activity estimated at Rp 487,12 trillion on average per year, or approximately 1,9% of GDP.                      Berkembangnya kegiatan underground economy diyakini berpotensi menyebabkan hilangnya penerimaan negara melalui sektor perpajakan. Penelitian ini dilakukan dengan tujuan untuk menganalisis dan mengetahui besarnya nilai kegiatan underground economy regional di Indonesia pada periode 2011 s.d. 2015 dan besarnya potensi pajak yang hilang akibat adanya kegiatan underground economy tersebut. Dengan menggunakan data sekunder berbentuk runtut waktu (time series) triwulanan dari rilis publikasi Bank Indonesia (BI), Badan Pusat Statistik (BPS) dan Direktorat Jenderal Pajak Kementerian Keuangan dan metode analisis kuantitatif yang diestimasi dengan metode Ordinary Least Square (OLS) serta perhitungan estimasi underground economy menggunakan pendekatan moneter yang dikonstruksi oleh Vito Tanzi (1980) dan Faal (2003), penelitian ini secara empiris mengestimasi nilai underground economy. berkisar antara Rp 289 triliun sampai Rp 958 triliun dengan nilai rata-rata mencapai Rp 536 triliun per tahun atau setara dengan 22,1% terhadap PDB Nominal. Sementara itu, akibat adanya kegiatan underground economy, potensi pajak yang hilang berkisar antara Rp 23,32 triliun hingga Rp 1.467 triliun dengan rata-rata per tahun mencapai Rp 487,12 triliun atau setara dengan 1,9% dari PDB.

scholarly journals Electricity Demand in Pakistan: A Household Analysis

2019 ◽  
Vol 1 (2) ◽  
pp. 34-39
Author(s):  
Nauman Ahmed ◽  
Uzma Nisar
Keyword(s):  
Urban Areas ◽  
Positive Impact ◽  
Least Square ◽  
Economic Determinants ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Time Period ◽  
Increasing Demand ◽  
Residential Demand ◽  
Household Analysis

Availability of electricity is essential in modern age because it becomes a necessity of life. The present study used some economic and non-economic determinants that affect household demand for electricity. This study used PSLM survey data for the year 2013-14. The amount of electricity consumed by household was used as dependent variable whereas electricity price, household income, appliances, heating days, region, awareness, and rooms were taken as explanatory variables. Ordinary least square technique (OLS) was used for analysis. The findings of the study showed that Economic and demographic factors are important in determining electricity expenditure. In micro level analysis prices has strong and positive effect on electricity expenditures and it didn’t represent traditional behavior of demand with price. Price and income had positive impact during the period of study with demand for electricity. Expenditure on electricity is fairly higher during summer season. Positive and significant effect is estimated for stock of electricity appliances. Household members have significant effect on electricity expenditure but shows very smaller influence. The dummy variable for region indicates that electricity expenditure is higher for those households who are living in urban areas as compared to rural. Over the time period residential demand of electricity is increasing in Pakistan. As Pakistan is consumption oriented society and demand for appliances is increasing so government should take necessary measures to shift appliances on other resources other than electricity. Increasing use of the appliances increases demand for electricity therefore generation of electricity resources should be increased to meet this increasing demand.

scholarly journals Luther Burbank’s Best Berries

HortScience ◽  
2015 ◽  
Vol 50 (2) ◽  
pp. 205-210
Author(s):  
Kim E. Hummer ◽  
Chad E. Finn ◽  
Michael Dossett
Keyword(s):  
Pacific Northwest ◽  
The United States ◽  
Human Consumption ◽  
Department Of Agriculture ◽  
Wide Crosses ◽  
Fruit Species ◽  
Small Fruit ◽  
Or Gene ◽  
Noxious Weed ◽  
The U.S

Luther Burbank, the quintessential nurseryman of the early 20th century, remarked that small fruit was the “Cinderella of the pomological family.” He stated that although tree fruits had been improved to the point of an almost uncountable number of cultivars, it was the time and responsibility of his generation and those to follow to develop the small fruit for human consumption. Burbank had a penchant for detecting potential qualities of unusual plants and his broad association with plant explorers at the U.S. Department of Agriculture and elsewhere allowed him to examine diverse wild berry species. He obtained seeds of many small fruit species from throughout the world. He made wide crosses within and between these genera and species. Burbank selected and named many cultivars to be introduced through his nursery and elsewhere. He named and released ≈40 blackberries, raspberries (Rubus L.), and strawberries (Fragaria L.); four grapes (Vitis L.); and a hybrid Solanum that he named ‘Sunberry’. He sometimes exaggerated their descriptions for promotion or public recognition. For example, Rubus ×loganobaccus ‘Phenomenal’ was, he stated, “far superior in size, quality, color, and productivity…” to ‘Loganberry’. Unfortunately, this cultivar was not a commercial success. Burbank made a few crosses and sold what he considered to be improved species, e.g., ‘Himalaya Giant’ blackberry (R. armeniacus). He created new common names for foreign species, e.g., balloon berry (R. illecebrosus) and Mayberry (R. palmatus), to better market them. However, his amazingly keen observations of thornlessness, pigment diversity, and recognition of repeat flowering and fruiting in blackberries, raspberries, and strawberries, were insightful of the needs of future industry. Burbank was a disciple of Darwin and his theory of natural selection. Burbank’s classic breeding approach, to make wide crosses, produce large numbers of hybrid seedlings, choose significant seedlings with his traits of choice, and backcross to the desired parent for several generations, was successful, although he did not know of ploidy or gene recombination. Unfortunately, the ‘Himalaya blackberry’, now ubiquitous in hedgerows and fields throughout the Pacific Northwest in the United States, is designated as a federal noxious weed. Although not presently in commercial production, three of his Rubus cultivars (‘Burbank Thornless’, ‘Snowbank’, and ‘Phenomenal’) are preserved in the U.S. Department of Agriculture, National Clonal Germplasm Repository, in Corvallis, OR.

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