Case Study-AW-Q234

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CASE STUDY
 
BACKGROUND INFORMATION
 
This is a study to predict the average volume of fixed deposit (FD) held by the public on a quarterly basis from different areas (metropolitan, city or town). The equation in the multiple regression is a demand relationship, and we would expect the dependent variable to depend on total personal wealth, on the interest rate that individuals receive when part of that wealth is invested in a fixed deposit, and so on. The primary interest rate on fixed deposit (RFDP) was therefore chosen as an explanatory variable. However fixed deposit must compare with other interest-bearing assets such as government bonds. Thus, the interest rates on government bonds (RGB) and are also explanatory variables; when this variable increase, the total demand for fixed deposit should decrease. Finally, the lagged dependent variable is also introduced to reflect lags.
 
Since the volume of fixed deposit, as well as many other financial variables, displays a seasonal behavior, a set of seasonal dummy variables is introduced to explain as much of this seasonal behavior as possible. The seasonal variables take the form of quarterly dummy variables multiplied by personal income. Since the first seasonal variable takes on the value of 1 in first quarter and 0 otherwise, the first seasonal variable takes on the value of personal wealth in first quarter. There are a total of 4 seasonal variables in the model, and the constant term should be drop to eliminate the collinearity problem.
 
Being a consultant of Ministry of Finance, you are required to perform some data analysis on the demand of fixed deposit. The relevant data has been provided to you by the ministry in Appendix 1 and 2.
Instructions
 
Use at least three of the following appropriate quantitative management techniques to examine and analyse a particular aspect of the case study
 
(i) One-sample / two-sample t-test for difference
(ii) Chi-squared test for independence
(iii) Correlation / simple or multiple linear regression
(iv) Fixed effect factor model/Random effect factor model
(v) Factor analysis/Structural equation modelling
(vi) Forecasting techniques
 
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Case Approach

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Write a report, with a maximum of 1500 words, that tackles the following tasks
 
(a) Introduction
Briefly describe the case study, identify the area/issue to be investigated, and explain its importance.
(10 marks)
 
(b) Aims, objectives and hypotheses
Identify the main aims, objectives of the study and formulate THREE difference hypotheses to be tested.
(11 marks)
 
(c) Findings & Discussions
Demonstrate the applications of suitable quantitative management techniques in the testing of these three difference hypotheses. The goal is to describe the data measured and the analyses performed as indicated based on the hypotheses. Tables and charts need to be labelled and numbered for easy reference (at least must have four tables/charts). Each chart or table should be able to stand on its own and tell its own story. Descriptions of the analysis methods should be complete so that the reader can assess the validity of your methods. You need to include a description of what was being tested, the statistical methods used and any assumptions that were made. You do not need to include all your output, but select the output that supports your conclusions. Interpret all the findings. You should include any explanations you may have for what you have found in the data.
(45 marks)
 
(d) Conclusions & Recommendations
Draw conclusions (e.g: which factors give a high impact on the demand of the fixed deposit and etc…) and make recommendations. What are the limitations of the analysis? Where appropriate, identify areas for further investigations/study.
 
(20 marks)
 
(e) Reference
Use proper referencing.
(2 marks)
 
(f) Appendix
Use proper appendix to enhance report presentation. It may include the data and output of SPSS. Also include data view and variable view from SPSS.
(2 marks)
 
(g) Presentation, structure, organisation and writing styles
The report presentation, structure and organisation. The writing styles in the report include the language used, proper grammar and spelling.
(10 marks)
 
APPENDIX 1 – VARIABLES
 
Area : the area that the banks located
RFDP : primary interest rate on fixed deposit (%)
FD : average of fixed deposit per account (RM ‘000)
PW : average personal wealth (RM ‘000)
RGB : interest rates on government bonds (%)
 
APPENDIX 2 – Data
 
 

Time Area RFDP FD PW RGB
2005Q1 Metropolitan 4.5 28 260 3.2
2005Q1 City 4.5 15 200 3.2
2005Q1 Town 4.5 5 120 3.2
2005Q2 Metropolitan 4.5 27 270 2.9
2005Q2 City 4.5 14 203 2.9
2005Q2 Town 4.5 5 123 2.9
2005Q3 Metropolitan 4.7 26 280 3.2
2005Q3 City 4.7 14 208 3.2
2005Q3 Town 4.7 6 124 3.2
2005Q4 Metropolitan 4.6 25 292 3
2005Q4 City 4.6 13 210 3
2005Q4 Town 4.6 6 127 3
2006Q1 Metropolitan 4.6 27 301 3.1
2006Q1 City 4.6 14 215 3.1
2006Q1 Town 4.6 6 129 3.1
2006Q2 Metropolitan 4.55 25 310 2.75
2006Q2 City 4.55 13 218 2.75
2006Q2 Town 4.55 6 131 2.75
2006Q3 Metropolitan 4.55 26 325 2.95
2006Q3 City 4.55 14 220 2.95
2006Q3 Town 4.55 5 133 2.95
2006Q4 Metropolitan 4.55 25 332 3.2
2006Q4 City 4.55 13 225 3.2
2006Q4 Town 4.55 4 134 3.2
2007Q1 Metropolitan 5.1 30 339 3
2007Q1 City 5.1 18 228 3
2007Q1 Town 5.1 10 135 3
2007Q2 Metropolitan 5.1 32 345 3.1
2007Q2 City 5.1 19 230 3.1
2007Q2 Town 5.1 10 129 3.1
2007Q3 Metropolitan 4.9 31 350 2.75
2007Q3 City 4.9 17 232 2.75
2007Q3 Town 4.9 9 134 2.75
2007Q4 Metropolitan 4.75 23 360 2.9
2007Q4 City 4.75 14 235 2.9
2007Q4 Town 4.75 7 138 2.9
2008Q1 Metropolitan 4.75 24 367 2.95
2008Q1 City 4.75 15 238 2.95
2008Q1 Town 4.75 8 140 2.95
2008Q2 Metropolitan 4.9 32 369 2.75
2008Q2 City 4.9 17 240 2.75
2008Q2 Town 4.9 9 142 2.75
2008Q3 Metropolitan 4.9 29 371 2.95
2008Q3 City 4.9 18 242 2.95
2008Q3 Town 4.9 10 144 2.95
2008Q4 Metropolitan 4.82 24 373 3
2008Q4 City 4.82 17 250 3
2008Q4 Town 4.82 8 145 3
2009Q1 Metropolitan 4.82 23 380 2.9
2009Q1 City 4.82 16 251 2.9
2009Q1 Town 4.82 8 146 2.9
2009Q2 Metropolitan 4.73 22 390 3.1
2009Q2 City 4.73 15 253 3.1
2009Q2 Town 4.73 7 148 3.1
2009Q3 Metropolitan 4.66 22 402 3.2
2009Q3 City 4.66 15 255 3.2
2009Q3 Town 4.66 6 149 3.2
2009Q4 Metropolitan 4.75 24 410 2.95
2009Q4 City 4.75 14 256 2.95
2009Q4 Town 4.75 7 150 2.95
2010Q1 Metropolitan 4.6 23 417 3.1
2010Q1 City 4.6 13 257 3.1
2010Q1 Town 4.6 7 151 3.1
2010Q2 Metropolitan 4.58 23 421 2.75
2010Q2 City 4.58 12 260 2.75
2010Q2 Town 4.58 6 152 2.75
2010Q3 Metropolitan 4.7 26 425 2.95
2010Q3 City 4.7 14 262 2.95
2010Q3 Town 4.7 7 153 2.95
2010Q4 Metropolitan 4.7 25 430 3
2010Q4 City 4.7 15 264 3
2010Q4 Town 4.7 7 153 3
2011Q1 Metropolitan 4.75 24 440 2.85
2011Q1 City 4.75 15 265 2.85
2011Q1 Town 4.75 8 154 2.85
2011Q2 Metropolitan 4.65 23 450 3.2
2011Q2 City 4.65 15 266 3.2
2011Q2 Town 4.65 6 155 3.2
2011Q3 Metropolitan 4.5 22 453 2.85
2011Q3 City 4.5 15 267 2.85
2011Q3 Town 4.5 5 157 2.85
2011Q4 Metropolitan 4.45 21 451 2.9
2011Q4 City 4.45 14 270 2.9
2011Q4 Town 4.45 4 158 2.9
2012Q1 Metropolitan 4.45 21 462 2.85
2012Q1 City 4.45 15 271 2.85
2012Q1 Town 4.45 4 160 2.85
2012Q2 Metropolitan 5 33 467 2.75
2012Q2 City 5 18 273 2.75
2012Q2 Town 5 10 162 2.75
2012Q3 Metropolitan 4.75 25 469 3
2012Q3 City 4.75 17 275 3
2012Q3 Town 4.75 7 163 3
2012Q4 Metropolitan 4.58 21 474 2.95
2012Q4 City 4.58 16 276 2.95
2012Q4 Town 4.58 5 163 2.95
2013Q1 Metropolitan 4.5 24 480 2.85
2013Q1 City 4.5 15 278 2.85
2013Q1 Town 4.5 5 164 2.85
2013Q2 Metropolitan 4.3 22 482 2.9
2013Q2 City 4.3 15 280 2.9
2013Q2 Town 4.3 3 165 2.9
2013Q3 Metropolitan 4.6 23 485 3
2013Q3 City 4.6 14 281 3
2013Q3 Town 4.6 6 166 3
2013Q4 Metropolitan 4.6 24 490 2.85
2013Q4 City 4.6 13 282 2.85
2013Q4 Town 4.6 5 167 2.85
2014Q1 Metropolitan 4.48 23 493 3.2
2014Q1 City 4.48 12 284 3.2
2014Q1 Town 4.48 4 168 3.2
2014Q2 Metropolitan 4.48 24 496 2.95
2014Q2 City 4.48 12 286 2.95
2014Q2 Town 4.48 4 170 2.95
2014Q3 Metropolitan 4.75 24 501 2.85
2014Q3 City 4.75 14 288 2.85
2014Q3 Town 4.75 7 171 2.85
2014Q4 Metropolitan 4.6 24 503 3
2014Q4 City 4.6 14 292 3
2014Q4 Town 4.6 6 172 3

 

 

 
Product Code-Case Study-AW-Q234
 
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