Dear all, I matched a set of company (tem1_tic) with another set of company (tic) by year, industry (sic) and closest_size (see attached). However, there are many matched firms for every tem1_tic. I wish only have one matched firm for each tem1.tic. I wish to select the first matched firms. However, a condition that I have to consider is that: some matched firms might be the matched firm of another tem1.tic. My question is that: how to ensure that I will have one unique matched firm for every tem1.tic with the following conditions? 1. the matched firm must not be selected as matched firm for another tem1.tic. 2. If there is the only (1) matched firm for a given tem1.tic, that matched firm must be selected as matched firm, in priority. I am thinking to solve the problem by sorting the data into the number of matched firms, then select the firms according to the priority condition, with firms with lowest number of matched firms should be matched earlier. I also wish to know firms that do not have any matched firm, as their match firm might have been a matched firm of another firms (in priority)? Thank you. Regards, Mspak ... View more

Dear all, I ran the following program (propensity score matching): proc sort data=test out=full ; by descending tem; run; proc probit data=FULL noprint;    class TEM;    model TEM = FREQ SHARES NUMEST BONUS_PERCENT1 BLACK_OPTION1 ROA1 LG_ASSET MB IND01-IND10 YeaR03 - YeaR09 / lackfit;    output out=regdata_out xbeta=gammaw p=pred;     run; data GD1 GD0; set regdata_out; if TEM = 1 then output GD1; if TEM = 0 then output GD0; run; proc sql; create table temp as select a.tic as TEM1_tic, a.fyear as tem1_fyear, b.*, abs(sum(a.pred, -b.pred)) as diffPS, min(calculated diffPS) as closest_PS from GD1 a , GD0 b group by a.tic, a.fyear having diffPS = closest_PS; quit; proc sql; create table temp_tem1 as select a.* from GD1 a, temp b where a.tic = b.TEM1_tic and a.fyear = b.tem1_fyear; quit; data matchpair; set temp_tem1 temp(drop = tem1_tic); run; But I could not get the output as it consumes a lot of processing time and a large storage. I am not sure whether there is a more efficient way to obtain the same output as the program above? Thank you. Regards, mspak ... View more

Good days to all, I have a SAS file with the following variables: hk_id = identification code for each IPO (Initial Public Offering) firm Industry = Industry for each firms underwriters_id = identification code for underwriters involved underwriters = Classified as either "MAIN UNDERWRITER" or "CO-UNDERWRITER" I wish to calculate the following variable: Number of IPOs in the same industry that the underwriters involved in the dataset = same_ind My expected output: hk_id Industry underwriters_id industry same_ind av_same_ind For example, the IPO firm with hk_id=2, Industry =Basic Materials; 3 underwriters involved ib002, ib003 and ib005. I would wish to know how many times each of the underwriter (ib002, ib003 and ib005) handled IPOs (based on the sample given)Basic Materials" industry (same_ind). Then, I will output the average times in which all the underwriters for each firm handled the IPOs in the same industry (av_same_ind). av_same_ind is calculated as sum of same_ind of all underwriters for each IPO firm/number of underwriters involved in the IPO.  Thank you in advance for any advices. Regards, mspak   ... View more

Dear all, I downloaded data from 2 different databases with different their identification codes. As such, it is impossible to match cases by an ID. Therefore, the only way is to match the cases by using their company names which is an inexact character variable. I have 2 different datasets: A) uw_match, with the following variables: - underwriters_names; - holding_company; - ipo_date; - others..... B) maluw, with the following variables; - name (label as bank name) - bs_id_number (bankscope identification code) - closdate (Company Fiscal Year End) - others.... I wish to match-merge these two dataset by the following creteria: STEP 1: the underwriters (either underwriters_names or their holding_company) in dataset A compared to bank name in dataset B; note: I can either match-merge the underwriters_names (in A) with the bank name (in B) or holding_company (in A) with bank name (in B), the pairs with the higher matching accuracy level will be output/used; AND STEP 2: the closest  closdate (in B) with ipo_date (in A). In short, I wish to match all the variables in A and B, by 1. the bank names (in B) = IPO underwriters (in A; either underwriters_names or their holding_company;which can provide the highest precision level) 2. in the similar period (ie. the closest fiscal year end of the banks with the IPO date). I read an article (see the pdf attached), and I understand that it is possible with SAS. But I feel little knowledge on how to apply the examples into my context here. Any comment and advise is much appreciated. Thank you. Regards, mspak ... View more