CHAPTER on manufacturing company’s performance in Malaysia. This research

CHAPTER 3 METHODOLOGYINTRODUCTIONIn this research, it will focus on the effect ofworking capital management on manufacturing company’s performance in Malaysia.This research wills using 10 years’ and 30 companies listed in SMEsmanufacturing in Malaysia. Therefore, the period of study started from 2006until 2017. The data collection is from a DataStream in Faculty Economic andBusiness (FEB), UNIMAS. The objective of the study is to analyses the workingcapital management on firm’s performance toward Malaysia economic. In this part, it will explain more on the method thatwill be using in test the hypotheses and also will describe the model to beusing for this study. This chapter divided into five sections: research design,estimate model, measurement, and statistical data analyses.

The statisticaldata analyses divide into three proxies: diagnostic test, descriptive analysesand panel regression. For the diagnostic test, it test the hypotheses whetherit significant or inversely result. Then, the descriptive analysis is a summarizea given data set. Lastly, the panel regression is data that collect over timefor companies listed in SMEs manufacturing.    RESEARCHDESIGNBased on the research, it’s about the effect ofworking capital management on firm’s performance toward manufacturing companyin Malaysia. The dependent variable is the firm’s performance while independentvariable is the working capital management. Both of the variables are relatedto SMEs manufacturing performance. This study is using the secondary data whichquantitative approach in order to analysis and collect data with 300 samplesobservation of listed SMEs manufacturing company in Malaysia.

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            Thegap period will be analysis from 2006 until 2017 and companies will take fromSMEs manufacturing company in Malaysia. In year 2008 was been chosen becausethere was the Asian financial crisis. Due to the financial crisis, themanufacturing sector is the ones that easier to faces the bankruptcy. Plus, thecollection data will be using the DataStream at Faculty Economic and Business,UNIMAS and also using STATA software. Consequently, this study is using the panelregression analysis which combination between time series and cross-section.Thus the test will be using are Normality test, Multi collinearity test,Autocorrelation test, Heterokedasticity test, Breusch-Pagan LM Test, and Hausmantest.    ESTIMATIONMODELThe accurate about relationship between company returnand factor that influence of exogenous variable based on multifactorialregression analysis. Using the specialized software, Eviews 9 is to identifysome econometrics models.

  Thus, the y isthe dependent variable, while, x is independent variable known as exogenousvariable that influence the endogenous variable and  is the stochastic. Below is an example ofgeneral form of equation:Therefore, the effect of working capital management onfirm performance in this research equation is:Where,  is the financial firm performance as measureby return on assets with  is time series () and  is the cross section  is intercept or constants variable thatinfluences firm performance1-4 are thepredictor coefficient that effect the , dependent variable is represent the cash management as cash ratio is represent the inventory management asinventory conversion period is represent the receivable management asaccounts receivable period is represent the payable management asaccounts payable management is represent the cash conversion cycle is the error term of stochastic            Toidentify model to the series of statistical tests regarding of coefficients,the significant level of the variables for the analyze phenomenon, the presenceof multicollinearity, the residual variable quality, the accuracy of model mustbe done by using  acceptance ofregression equation for analysis.            Thepurpose of using panel data analysis to understands variability of the timeseries and cross sectional. Furthermore, this kind model can identify theregular and irregular oscillations of the panel data.

Also, this can describethe characteristics of oscillation and the physical process that give rise toeach of oscillation.