{smcl} {* December 2006}{...} {* Updated September 2007, August 2008, May 2009} {hline} {cmd:help for wdireshape} {hline} {title:Title} {p 4 8 2} {bf:wdireshape --- Reshapes the World Development Indicators (WDI) database for panel data, seemingly unrelated regression, or cross-sectional analysis} {marker contents}{dlgtab: Table of Contents} {p 6 16 2} {p 2}{help wdireshape##syntax:Syntax}{p_end} {p 2}{help wdireshape##description:General description of {cmd:wdireshape}}{p_end} {p 2}{help wdireshape##options:Description of the options}{p_end} {p 2}{help wdireshape##examples:Examples}{p_end} {p 2}{help wdireshape##refs:References}{p_end} {p 2}{help wdireshape##acknow:Acknowledgments}{p_end} {p 2}{help wdireshape##author:Author information}{p_end} {hline} {marker syntax}{title:Syntax} Check the number of indicators and their order of appearance in a WDI dataset {phang}{cmd: wdireshape,} {opth sername(varname)} Reshape the dataset {phang} {cmd: wdireshape} {help newvarlist}{cmd:,} {cmdab:prep:end(}{it:letter(s)}{cmd:)} {opth ctyn:ame(varname)} {opth sern:ame(varname)} {opth ctyc:ode(varname)} {opth serc:ode(varname)} [{it:{help wdireshape##options:other options}}] {synoptset 20 tabbed} {synopthdr} {synoptline} {syntab:Options} {synopt :{cmdab:prep:end(}{it:letter(s)}{cmd:)}}indicate the prepending letter(s){p_end} {synopt :{opth ctyn:ame(varname)}}indicate the variable holding the country names{p_end} {synopt :{opth sern:ame(varname)}}indicate the variable holding the series names{p_end} {synopt :{opth ctyc:ode(varname)}}indicate the variable containing the country code elements{p_end} {synopt :{opth serc:ode(varname)}}indicate the variable holding the series code elements{p_end} {synopt :{opt byp:er(#)} }reshape the data using sub-periods{p_end} {synopt :{opt start:yr(#)}}indicate the first year of the time period{p_end} {synopt :{opt end:yr(#)}}indicate the last year of the time period{p_end} {synopt :{opt byv:ar}}reshape the data variable by variable{p_end} {synopt :{opt sur}}reshape in wide form for seemingly unrelated regression analysis{p_end} {synopt :{opt cros}}reshape in wide form for cross-sectional analysis{p_end} {synopt :{opt ns:tring(#)}}remove the WDI missing value symbols, the double dots (..){p_end} {synoptline} {p2colreset}{...} {marker description}{dlgtab:Description} {pstd}{cmd:wdireshape} reshapes a Stata dataset obtained by insheeting a text (.csv) file downloaded from the World Development Indicators (WDI) website or extracted from the WDI CD-ROM. The new dataset has a structure suitable for panel-data analysis, seemingly unrelated regression (SUR), or cross-sectional modeling. The panel-data structure is known as long form and the SUR and cross-sectional structures are known as wide form. {cmd:wdireshape}, a wrapper for the Stata's official {cmd:reshape} command (see {help reshape}), enables users to rename the indicators with names of their devising. However, the number of variable names supplied and their order must match those of the indicators in the spreadsheet. After insheeting the raw dataset to be reshaped, users can use the first syntax of {cmd:wdireshape} to determine the number of indicators as well as their order of appearance in the dataset. While reshaping the data, {cmd:wdireshape} places the WDI series descriptors into labels and attaches them to the user-supplied variable names. Note that, for long series descriptors, labels will be truncated to 80 characters.{p_end} {marker remarks}{dlgtab:Important Remarks} {pstd}Before extracting a .csv file from the WDI web site or a recent CD release, users must choose a data orientation with series or countries in rows and time in columns. A WDI dataset downloaded using this orientation is ready to be insheeted since the years are prepended with two letters "yr". Thus, no data preparation is needed. However, the WDI missing value symbols, the double dots (..), must be removed. Otherwise, Stata will treat as string data in any columns containing those double dots. At the users' request, {cmd:wdireshape} will remove the double dots. {p_end} {pstd}Older CD releases, such as the WDI-2005 CD-ROM, produce .csv files that must be managed prior to insheeting. In particular, the years must be prepended with a letter, which can be done in a spreadsheet or by using the procedure suggested in Baum and Cox (2007). The raw or prepared dataset saved as a .csv file can be imported into Stata using the {cmd:insheet} command as follows:{p_end} {cmd:. insheet using} {it:filename.csv}, {cmd:names clear} {phang}Data may also be imported into Stata by copying from Excel and pasting directly into the Stata data editor.{p_end} {marker options}{dlgtab:Required options} {pstd} {cmd:prepend(}{it:letter(s)}{cmd:)} specifies the prepending letter(s). For example, specify {opt prepend(yr)} if {hi:yr} are the prepending letters. {pstd} {opth sername(varname)} specifies the variable holding the series names. {pstd} {opth ctyname(varname)} specifies the variable containing country names. {pstd} {opth ctycode(varname)} specifies the variable containing the country code elements. {pstd} {opth sercode(varname)} specifies the variable containing the series code elements. {pmore} With these required options specified, {cmd:wdireshape} will attempt to reshape the entire dataset at once, which is the default. {marker options}{dlgtab:Optional options} {phang} {opt byper(#)} requires {cmd:wdireshape} to reshape the dataset 1 year, 5 years, or 10 years at a time, as long as the time span contains no gaps. One of these three values should be used with the {opt byp:er(#)} option. If either 5 or 10 is specified, {cmd:wdireshape} will account for the fact that the last subperiod may not be of 5 or 10 years. Also, Stata will check whether the current memory size is enough to reshape the data 5 or 10 years at a time.{p_end} {phang} {opt startyr(#)} specifies the first year of the time period. {phang} {opt endyr(#)} specifies the last year of the time period. {pmore}{hi:Note 1:} The {opt byper(#)}, {opt startyr(#)}, and {opt endyr(#)} options must be combined.{p_end} {phang} {opt byvar} specifies that the dataset to be reshaped one variable at a time, as proposed by Kossinets (2006). The {opt byvar} option may not be combined with {opt byper(#)}, {opt startyr(#)}, and {opt endyr(#)}.{p_end} {pmore} Due to memory issues, reshaping large datasets at once may not be successful. In such a case, Stata will prompt the user to specify the {cmd:byvar} or {cmd:byper(#)} option, or to increase the amount of memory allocated to Stata. Note that you can reset the size of memory only if you are using {help statamp:Stata/MP}, {help specialedition:Stata/SE}, or {help stataic:Stata/IC}.{p_end} {phang} {opt sur} requests a wide form suitable for SUR analysis (see {help SUREG}). By default, the dataset is reshaped in long form for panel data analysis (see {help XTREG}). When the {opt sur} option is specified, in the reshaped dataset, the country names are postfixed to the user-supplied variable names and are represented by c1, c2, and so. {cmd:Describe} the reshaped dataset if you want to know what countries c1, c2,...,cn represent. In Stata 10 or higher, you can just look at the variable labels in the variable window. The SUR-reshaped structure displays the years in rows and the variables, for each country, in columns. {phang} {opt cros} requests a wide form amenable to cross-sectional analysis. The CROS-reshaped structure displays the country names in rows and the variables, for each year, in columns. Obviously, {opt cros} may not be combined with {opt sur}. {pmore} {hi:Note 2:} When the {opt sur} or {opt cros} option is specified, Stata will complain if the resulting number of variables exceeds its limits, which are 99 for small Stata, 2047 for intercooled, and 32,767 for Stata/MP and Stata/SE. {phang} {opt nstring(#)} indicates that the dataset contains the WDI missing value symbols, the double dots (..), and that they should be removed. # represents the number of identifier variables in the dataset. For example, {opt nstring(4)} must be specified when the dataset includes names and code elements for both countries and series as identifier variables. When the {opt nstring(#)} option is specified, if an error occurs for any reasons, the dataset to be reshaped needs to be reloaded before running {cmd:wdireshape} again. Otherwise, Stata will abort with a type-mismatch error. {pmore} {hi:Note 3:} Depending on your computer system performance, in case of large datasets, reshaping 10 years at a time - as long as the time period is at least 10 years - may be faster than reshaping variable by variable. However, when the time period contains gaps, the {opt byper(#)} option will not work. {marker examples}{dlgtab:Examples} Check the number of indicators and their order of appearance in a WDI dataset {phang}{cmd:. wdireshape, sername(seriesname)} Reshape the entire dataset at once {phang}{cmd:. wdireshape v1-v10, prepend(yr) ctyname(countryname) sername(seriesname) ctycode(countrycode) sercode(seriescode)} {phang}{cmd:. wdireshape gdpcap trade invest cropland tractor popdensity arable, prepend(yr) ctyname(countryname) ///}{p_end} {bf: sername(seriesname) ctycode(countrycode) sercode(seriescode)} Reshape variable by variable {phang}{cmd:. wdireshape export import gdpcur gdpcnst foodindx irrig, prepend(yr) ctyname(countryname) ///}{p_end} {bf: sername(seriesname) ctycode(countrycode) sercode(seriescode) byvar} Reshape 5 years at a time {phang}{cmd:. wdireshape myvar1-myvar16, prepend(yr) ctyname(countryname) sername(seriesname) ctycode(countrycode) ///}{p_end} {bf: sercode(seriescode) byp(5) start(1960) end(2004)} Reshape 10 years at a time, but for SUR analysis {phang}{cmd:. wdireshape myvar1-myvar16, prepend(yr) ctyname(countryname) sername(seriesname) ctycode(countrycode) ///}{p_end} {bf: sercode(seriescode) byp(10) start(1960) end(2004) sur} {hi:Note 4:} To obtain series of averages, first run {cmd:wdireshape} without specifying the {opt sur} or {opt cros} option, and then run {cmd:paverage} (see {help paverage} if installed) {marker refs}{title:References} Baum, C.B. and N.J. Cox. 2007. Getting those Data into Shape. {it:Stata Journal} 7: 268-271 Kossinets, G. 2006. {browse "http://www.columbia.edu/acis/eds/data_tools/tips/reshape_manyvar.do":http://www.columbia.edu/acis/eds/data_tools/tips/reshape_manyvar.do} The World Bank Group. 2009. {it:World Development Indicators (WDI) Online}. {browse "http://publications.worldbank.org/WDI/":http://publications.worldbank.org/WDI/} {marker acknow}{title:Acknowledgments} Thanks to Kit Baum for useful comments. Thanks to Simon Feeny for pointing out the need to allow for quotes in the WDI series descriptors. {marker author}{title:Author} {p 4 4 2}{hi: P. Wilner Jeanty}, Dept. of Agricultural, Environmental, and Development Economics,{break} The Ohio State University{break} {p 4 4 2}Email to {browse "mailto:jeanty.1@osu.edu":jeanty.1@osu.edu} for any comments or suggestions. {title:Also see} {p 4 13 2}Manual: {hi:[D] reshape} {p 4 13 2}Online: {helpb reshape}, {helpb insheet}