. CHAPTER 4: RESULTS AND DICUSSIONS 4.0 Introduction This chapter discusses the results of analysis on the topic of factors that affecting demand for Proton cars in Malaysia. Eviews with version 7 is used to run the data in order to do the analyses of particular test. The analysis embraces of the multiple regression analysis, bivariate correlation, standard error of coefficient (t-test), analysis of variance (F-test), p-value analysis, coefficient of determination, serial correlation ramsey RESET test, serial correlation, white’s heteroscedastic test and granger causality test. The empirical results are presented systematically as below. 4.1 Multiple Regression Analysis The multiple regression analysis is a technique of statistical for determining and modeling the relationship between dependent variable (DPC) and explanatory variables (INF, GDP and FP). It also explains how the DPC affected by INF, GDP and FP. Whereas, the multiple linear regression model is an analysis of relationship in which the effects of two or more independent variables on a single, interval scaled or ratio-scaled dependent variable are estimated at the same time (Gujariti and Porter, 2009). It is useful for demonstrating and interprets the truthful of empirical result. The double log model is chosen as empirical model in this study due to its coefficient of variation is smaller than other models (Table 6.4 in Appendix). It is linear in the logarithm of dependent and independent variables. Therefore, double log model is employed through Ordinary Least Square (OLS) method for determining the elasticity of dependent variable and independent variables. The empirical model of demand for Proton car can be represented as follows: (lnDPC) ̂=β_0+β_1 lnINF+β_2 lnG... ... middle of paper ... ...ignificant to the demand for Proton car. The evidence of the inflation was not a determinant of Proton cars sales is because of the Proton cars were sold at cheapest prices with high quality. Therefore, the Proton cars still increasing during the session of inflation due to the reason of the requirement of consumers has been achieved (Wan, 2013). For the independent variable of fuel price, it also does not granger cause the dependent variable of demand for Proton car. It means that the fuel price variable is no significant to the demand for Proton car. However, many studies discovered that the fuel price is a significant response to Proton demand. According to the Johansson and Schipper (1997), the vehicle types and distance driven were affected by the hike of fuel price. This means that the consumers still purchasing the vehicles when the fuel price increased.
To conclude this analysis, it can be noted that any increases in the prices of fuel will increase Australia’s economy as a whole, in other words the higher the costs of logistics will increase the price of products (Australian Competition & Consumer Commission 2014). The consumers will have to handle the burden of having higher costs of products, which would create an inflation. With the increasing price of fuel, consumers might want to alter their lifestyles, such as using public transportation or even carpooling. Vacations and travelling will also have to be cut down. Australia requires further government intervention to control the price of fuel by subsidizing so that inflation may be curbed.
In a simple regression model, we are trying to determine if a variable Y is linearly dependent on variable X. That is, whenever X changes, Y also changes linearly. A linear relationship is a straight line relationship. In the form of an equation, this relationship can be expressed as
Another key cause to the price inflation issue is the extended period of bitterly cold weather that loomed in the northern and midwestern parts of the U.S. throughout the winter months. This led to an “increased demand in home heating oil, which is widely used in the region and is virtually identical to diesel fuel” (Lang1). This increased demand for fuel coupled with the restrictions on exported oil allowed OPEC to jack up their prices an exorbitant amount in a relatively short period of time.
The procedures described here presume that the association between the independent and dependent variables is linear. With some modifications, regression analysis can also be used to estimate associations that go after another practical form (e.g., curvilinear, quadratic). Here we consider associations between one independent variable and one continuous dependent variable. The regression analysis is called simple linear regression - simple in this case refers to the fact that there is a single independent
This paper will describe three combinations of independent variables that could be used testing regression analysis and the difference between correlation and regression. It will also explain the outcomes of regression analysis, and how I could use these in my future career.
Within the last decade Apple has become one of the largest growing companies in the world and the largest valued company in the United States. According to a recent article in The Guardian, a global financial news website, “Apple set a record by becoming the first company to be valued at over $700bn (£446bn).” (Fletcher, N. 2014) This comes as no surprise to the average computer aficionado and shareholder as Apple has been making a name for itself since its inception. From its earliest Macintosh models to today’s iPhones, Apple has been a trailblazer for software, technology and revolutionizing the way we communicate on a Macro level. Their dedication to innovation, quality and service has made them
A vehicle is one of the biggest purchases a person will ever make. Over the years, the prices of an automobile have increased due to the rise of inflation. Due to a price index, the price of an automobile changes over a certain period of time. Economists compare averages of automobiles to calculate the cost of each vehicle that presents itself on a car lot. When all of the above is calculated within the purchase of an automobile, it affects every area of making the automobile to selling the automobile. All of these factors are impacted together for the automobile industry as a whole.
... Also important is the price of complements, or goods that are used together. When the price of gasoline rises, the demand for cars falls.
The article by Mike Moffatt shows the price elasticity of demand for gasoline. According to Molly Espey the average price elasticity of demand for gasoline in the short- run is-0.26 and -0.58 In the long-run, which is a 10% raise in the price of gasoline lowers quantity demanded by 2.6% in the short- run and 5.8% in the long- run.Also, there are a studies were conducted by Phil Goodwin, Joyce Dargay and Mark Hanly at review of income and price elastics in the demand for road traffic and each of them has different study. Furthermore, the realized elasticities depend on factors such as the timeframe and locations that the study covers. If the gas taxes will rise, will cause consumption to decrease.
One method that Toyota can consider is using the price elasticity of demand to determine whether to increase or decrease the sale price of their automobiles. The responsiveness or sensitivity of consumers to a price change is measured by a product's price elasticity of demand (McConnell & Brue, 2004). Market goods can be described as elastic or inelastic goods as change in quantity demanded for that good. If demand is elastic, a decrease in price will increase total revenue. Even though a lower price would generate lower sales revenue per unit, more than enough additional units would be sold to offset lower price (McConnell & Brue, 2004). In a normal market condition, a price increase leads to a decreased demand, and a price decrease leads to increased demand. However, a change in income affecting demand is more complex.
Finally, many car companies make more efficient cars and hybrid cars. Companies trying to boost their sales through efficient cars and lower gas cost for the consumer. Because of the higher prices of gas consumers are looking for more efficient cars. Gas prices left big companies like Ford, Toyota, and Dodge slow which it had a direct effect in the economy and the workforce. Many people lost their jobs over the passed six months because of the effect of the slow economy.
Price changes affect demand for various foods. According to the economic theory, consumption of a certain product falls as the price of that item rises...
Regression analysis is a technique used in statistics for investigating and modeling the relationship between variables (Douglas Montgomery, Peck, &
As Tata Motors is an automobile company, the raw materials required in production of a car or a vehicle include aluminium, copper, platinum, palladium, rhodium, steel and zinc. The prices for these materials have been increasing in the recent years. An increase in price of input materials could severely impact its profitability. Additionally, increases in fuel costs also pose a significant challenge to automobile manufacturers worldwide, especially in the commercial and premium vehicle segments where increased fuel prices have an impact on
The purpose of this essay is to provide a complete analysis of BMW Group. First, some background information about the company will be provided for a better comprehension of this study. Next, BMW will be assessed from a microeconomic point of view: its demand curve, organisational structure, customers, suppliers, strengths, weaknesses and its operating environment. Then, this firm will be reviewed in context of its sector from a macroeconomic perspective and more specifically its market environment, followed by a PEST analysis of other external factors such as GDP, interest rate, cost of raw materials. This study will be further quantified by a ratio analysis in order to evaluate BMW’s financial health. In the end you can find a conclusion and also a bibliography, which can be used as further reading material.