1 / 7

Econometric Analysis Using Stata

Econometric Analysis Using Stata. Introduction Time Series Panel Data. Time Series Analysis Using Stata. Declare time series data and variables tsset Time series operators L.; F.; D.; S. Commands with time series options regress …, if tin(.,.) generate summarize .

tawny
Download Presentation

Econometric Analysis Using Stata

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Econometric Analysis Using Stata Introduction Time Series Panel Data

  2. Time Series Analysis Using Stata • Declare time series data and variables • tsset • Time series operators • L.; F.; D.; S. • Commands with time series options • regress …, if tin(.,.) • generate • summarize

  3. Example: U.S. GDP Growth gdp2009.txt gdp2009.dta • Time series setup • Time series operators • Time series line plot (graphics) • Time series regression

  4. gdp1.do * Read text data file (.txt) and covert it to Stats dataset file (.dta) infile year quarter gdp gdpdef using “\course14\ec572\data\gdp2009.txt" describe summarize label data "U. S. GDP: 1947.1-2013.3" label variable gdp "GDP (billion of current dollars)" label variable gdpdef "Implicit GDP price deflator (year 2009 = 100)" * delete the 1st line of variable names drop in 1 * create a time series dataset generate time=yq(year,quarter) tsset time, quarterly label variable time "Time" drop year quarter describe summarize * save it as a Stata dataset, if it has not done yet save "\course14\ec572\data\gdp2009"

  5. gdp2.do * use graph to represent the data * a graph is worth of thousand words clear use http://web.pdx.edu/~crkl/ec572/data/gdp2009.dta * is this time series data? tsset d su * generate new variable gen rgdp=100*gdp/gdpdef gen lrgdp=ln(rgdp) gen gq=100*D.lrgdp gen ga=100*(lrgdp-L4.lrgdp) su * time series line plots tsline rgdp, name(rgdp) tsline gq ga, name(growth) * time regression reg lrgdp time

  6. Example: SP-500 sp500new.xml • Reading from an Excel XML database file • Time series (daily) data setup • Time series line plot (graphics) • Time series analysis

  7. sp500new0.do /* ** Time Series Analysis of U.S. SP500 Stock Market Index ** Latest update: 12/31/2013 ** Retrieve monthly data, converted from daily format */ clear set more off xmluse "\Course14\EC572\data\sp500new.xml", doctype(excel) sheet(Monthly) cells(A2:G769) clear save "\Course14\EC572\data\sp500m", replace gen date=var1 gen vol=var6 gen idx=var7 sort date drop var* gen month=mofd(date) tsset month, monthly gen r=100*(ln(idx)-ln(L.idx)) //gen r=100*(ln(idx)-ln(idx[_n-1])) summarize tsline idx, name(SP500m_INDEX,replace) tsline r, name(SP500m_Returns,replace) * Is IDX stationary? IDX~I(1) * Is R stationary? R~I(0) * ARMA and ARCH structures of R * SP500 Forecasts?

More Related