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Tutorial in Research Project Design

by: April Jerde

Tutorial in Research Project Design ECON 590

Marketplace > University of Wisconsin - Madison > Economcs > ECON 590 > Tutorial in Research Project Design
April Jerde
GPA 3.6

Kenneth West

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Kenneth West
Class Notes
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This 14 page Class Notes was uploaded by April Jerde on Thursday September 17, 2015. The Class Notes belongs to ECON 590 at University of Wisconsin - Madison taught by Kenneth West in Fall. Since its upload, it has received 33 views. For similar materials see /class/205138/econ-590-university-of-wisconsin-madison in Economcs at University of Wisconsin - Madison.


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Date Created: 09/17/15
Some basic data concepts and transformations percentage change log differences annualized levels and rates of change seasonal adjustment price indexes converting nominal to real exchange rate conversions Percentage change log differences repeated om overheads on Solow article Numerical example with FM 3 illustrating that log differences are approximately percentage growth A l 10 l1 102 ratio lll 102 growth 2 Aln 020 Apart from rounding K 200 206 103 3 030 N 100 106 106 6 058 YZAK13N23 1260 1349 1071 71 068 068 020 1303 23058 Mathematical reason log difference is approximately the same as percentage change a mean value expansion can be used to show that lnlx z x for x near zero So for growth in A for example lnl02 z 02 Annualized levels and rates of change Virtually all national income and product account data are collected and released quarterly eXpressed at annual rates seasonally adjusted released in both nominal and real terms Other collection and release frequencies are possible annually certain surveys of manufacturers monthly consumer price index and industrial production daily or even minute by minute nancial data such as stock prices httpwwwbeagov Real GDP change om previous quarter SAAR 20074 2008l 20082 20083 02 09 28 05 SAAR seasonally adjusted at annual rates annual rates Quarterly data nominal constructed by multiplying actual values by 4 GDP 20083 SAAR 14413 billion Actual GDP seas adjusted 144l34 3603 Monthly data multiplicative factor 12 Seasonal adjustment Removes predictable quarter to quarter or month to month variation in a series Most aggregate data are seasonally adjusted Exceptions nancial data interest rates exchange rates stock prices certain countries Seasonal adjustment continued Why seasonally adjust Illustrate With US nominal GDP data Nominal rather than real because US does not publish real data seasonally unadjusted 2006 rather than 2007 because seasonally unadjusted 2007 gures are not yet available Nominal GDP change from previous quarter 2006l 20062 20063 20064 Seas adj 86 55 36 37 Not seas adj 106 166 94 87 The fall of 106 from 20054 to 2006l does not indicate a recession but rather the usual effects of the Christmas induced spike in retail sales in quarter 4 as well as the effects of cold weather on construction agriculture etc Price index Prices in a base year are set to 100 If prices rise by say 08 per cent the rst quarter of the next year the price index is set to 1008 US national income and product account data currently use a base year of 2000 Nominal to real Real means effects of in ation are removed To convert nominal to real real nominal X 100 price index Nominal GDP SAAR in 20074 14031 billion Implicit price de ator 1208 Real GDP 2000 100gtlt140311208 11613 billion Example 2 using indexes and de ation S and P 500 stock price index Index 194143 10 Recent December values http nanceyahoocom 2001 2002 2003 2004 2005 2006 2007 2008 1148 879 1112 1212 1248 1418 1468 903 The index is constructed from the actual dollar value of the 500 stocks that comprise the index 2001 2002 2003 2004 2005 2006 2007 2008 1148 879 1112 1212 1248 1418 1468 903 To interpret these values Had you owned all 500 stocks in the index the value of your portfolio would have uctuated as follows in two representative years risen by 265 in 2003 because 1112 is 265 bigger than 879 risen by 30 in 2005 because 1248 is 30 bigger than 1212 fallen by 385 in 2008 because 903 is 385 smaller than 1468 These gures exclude dividend payments That is the nominal return was 265 in 2003 30 in 2005 and 385 in 2008 rate ofincrease during 2005 12481212 1030 nominal return 30 To compute the real return in 2005 using the implicit price de ator for GDP implicit price de ator 1145 in 20054 1107 in 20044 Method 1 S and P de ated Dec 2005 100gtlt12481145 1090 Dec 2004 100gtlt12121107 1095 real rate of fall 10901095 9955 real return 45 Method 2 approximate but easier to understand rate ofprice increase 11451107 1034 rate of in ation 34 real return z nominal return in ation 30 34 04 In this case the approximation is almost exact rate ofincrease during 2003 1112879 1265 nominal return 265 To compute the real return in 2003 implicit price de ator 1072 in 20034 1049 in 20024 Method 1 S and P de ated Dec 2003 100gtlt11121072 1037 Dec 2002 100gtlt8791049 838 real rate ofincrease 10378381238 real return 238 Method 2 approximate but easier to understand rate of price increase 107 2 1049 1022 rate of in ation 22 real return z nominal return in ation 265 22 243 rate of fall during 2008 9031468 0765 nominal return 385 To compute the real return in 2008 implicit price de ator 1231 in 20083 20084 data not yet available 1208 in 20074 For the sake of illustration assume the de ator will also be 1231 in 20084 Method 1 S and P de ated Dec 2008 100gtlt9031231 734 Dec 2007 100gtlt14681208 1215 real rate of fall during 2008 7341215 604 real return 396 Method 2 approximate but easier to understand rate ofprice increase 12311208 1019 rate of in ation 19 real return z nominal return in ation 385 19 404 Exchange rate conversions Sometimes expressed as units of foreign currency sometimes as unit of foreign currency Euro exchange rate 12309 078 129 This means People can get 1 for every 07 8 To purchase something that costs say 195 requires exchanging 078 gtlt 195 152 Or People can get 1 for every 129 To purchase something that costs say 195 requires exchanging 1 29 gtlt 195 251


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