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Posts: 73

Calculating wave of mergers

Dear Everyone,

I am trying to calculate wave in my study. I have included my real data in this post. In my data

Year=Year

Month=Month

Aindus48= Indicator variable for fama 48 industries

count=number of mergers in a particular month of a particular year in a particular industry.

I just copied the following section from the relevant article.

I split the sample into the 1980s, 1990s, 2000s and 2010s. Based on Mitchell and Mulherin (1996)'s study of two-year wave periods, waves in this study will be 24-months. Thus, for each industry, I calculate the highest 24-month concentration of merger bids involving firms in that industry in each decade.This 24-month period is identified as a potential wave. Taking the total number of bids over the entire decade for a given industry, I simulate 1000 distributions of that number of occurrences of industry member involvement in a bid over a 120-month period by randomly assigning each occurrence to a month where the probability of assignment is 1/120 for each month. I then calculate the highest 24-month concentration of activity from each of the 1000 draws. Finally, I compare the actual concentration of activity from the potential wave to the empirical distribution of 1000 peak 24-month concentrations. If the actual peak concentration exceeds the 95th percentile from that empirical distribution, that period is coded as a wave. Could anyone please give me the relevant code to find out the wave? I will appreciate your help.

My data set:

Month Year Aindus48 COUNT
1 1978 17 2
1 1979 19 1
1 1979 43 1
1 1980 13 1
1 1980 40 1
1 1981 7 1
1 1981 12 1
1 1981 14 1
1 1981 16 1
1 1981 17 1
1 1981 19 1
1 1981 21 1
1 1981 22 1
1 1981 28 1
1 1981 30 2
1 1981 32 1
1 1981 33 1
1 1981 35 2
1 1981 42 3
1 1981 44 5
1 1981 45 2
1 1981 47 1
1 1982 2 1
1 1982 14 3
1 1982 21 1
1 1982 30 1
1 1982 31 1
1 1982 34 1
1 1982 36 1
1 1982 42 2
1 1982 44 8
1 1982 45 1
1 1982 46 1
1 1982 47 1
1 1983 7 1
1 1983 13 1
1 1983 14 3
1 1983 15 1
1 1983 17 1
1 1983 21 2
1 1983 30 2
1 1983 34 3
1 1983 35 1
1 1983 36 4
1 1983 42 3
1 1983 43 1
1 1983 44 11
1 1983 47 1
1 1984 2 1
1 1984 7 2
1 1984 8 1
1 1984 9 1
1 1984 10 1
1 1984 11 2
1 1984 12 1
1 1984 17 3
1 1984 21 1
1 1984 23 1
1 1984 24 2
1 1984 29 1
1 1984 30 8
1 1984 31 1
1 1984 32 1
1 1984 34 3
1 1984 35 1
1 1984 36 3
1 1984 37 1
1 1984 39 1
1 1984 40 2
1 1984 41 1
1 1984 42 2
1 1984 43 2
1 1984 44 17
1 1984 45 6
1 1984 46 2
1 1984 47 1
1 1985 17 1
1 1985 21 1
1 1985 23 1
1 1985 24 1
1 1985 31 1
1 1985 34 1
1 1985 36 1
1 1985 38 1
1 1985 42 2
1 1985 44 2
1 1985 45 1
1 1985 47 1
1 1986 2 1
1 1986 3 1
1 1986 9 1
1 1986 14 1
1 1986 15 1
1 1986 34 2
1 1986 40 1
1 1986 42 2
1 1986 43 1
1 1986 44 4
1 1987 9 1
1 1987 18 1
1 1987 26 1
1 1987 30 1
1 1987 34 2
1 1987 35 1
1 1987 38 2
1 1987 41 1
1 1987 43 1
1 1987 44 8
1 1987 45 2
1 1987 47 2
1 1988 7 1
1 1988 9 1
1 1988 13 1
1 1988 17 1
1 1988 23 3
1 1988 31 1
1 1988 32 1
1 1988 34 1
1 1988 40 1
1 1988 41 1
1 1988 44 6
1 1989 2 1
1 1989 9 1
1 1989 10 1
1 1989 12 1
1 1989 13 2
1 1989 15 1
1 1989 21 1
1 1989 30 1
1 1989 32 3
1 1989 34 1
1 1989 42 2
1 1989 44 6
1 1989 45 1
1 1990 1 1
1 1990 2 1
1 1990 12 1
1 1990 13 1
1 1990 25 1
1 1990 31 1
1 1990 32 1
1 1990 34 3
1 1990 35 3
1 1990 36 2
1 1990 37 1
1 1990 38 1
1 1990 41 2
1 1990 44 4
1 1990 45 1
1 1990 47 1
1 1991 6 1
1 1991 7 1
1 1991 14 1
1 1991 16 1
1 1991 27 2
1 1991 30 1
1 1991 31 1
1 1991 34 2
1 1991 40 1
1 1991 41 1
1 1991 44 2
1 1991 45 1
1 1991 46 1
1 1992 2 1
1 1992 6 1
1 1992 11 5
1 1992 13 1
1 1992 14 1
1 1992 17 1
1 1992 19 1
1 1992 22 2
1 1992 23 1
1 1992 24 1
1 1992 32 3
1 1992 33 1
1 1992 34 6
1 1992 36 2
1 1992 40 2
1 1992 42 2
1 1992 43 1
1 1992 44 9
1 1992 45 1
1 1992 47 4
1 1992 48 3
1 1993 8 1
1 1993 11 1
1 1993 12 2
1 1993 13 1
1 1993 14 1
1 1993 21 1
1 1993 22 1
1 1993 27 1
1 1993 30 2
1 1993 31 1
1 1993 32 1
1 1993 34 1
1 1993 35 2
1 1993 36 5
1 1993 37 2
1 1993 39 1
1 1993 42 2
1 1993 43 2
1 1993 44 10
1 1993 45 2
1 1993 47 5
1 1993 48 2
1 1994 4 1
1 1994 7 1
1 1994 10 1
1 1994 11 6
1 1994 12 5
1 1994 13 1
1 1994 17 1
1 1994 18 1
1 1994 19 2
1 1994 23 1
1 1994 24 1
1 1994 30 5
1 1994 32 3
1 1994 34 8
1 1994 35 3
1 1994 36 4
1 1994 38 1
1 1994 40 1
1 1994 41 4
1 1994 42 4
1 1994 43 2
1 1994 44 19
1 1994 45 1
1 1994 47 3
1 1994 48 2
1 1995 7 4
1 1995 11 8
1 1995 12 1
1 1995 13 2
1 1995 14 2
1 1995 15 1
1 1995 16 1
1 1995 18 1
1 1995 19 1
1 1995 22 1
1 1995 31 2
1 1995 32 4
1 1995 33 1
1 1995 34 9
1 1995 35 1
1 1995 36 3
1 1995 37 1
1 1995 40 2
1 1995 41 5
1 1995 42 2
1 1995 43 1
1 1995 44 12
1 1995 45 3
1 1995 47 3
1 1996 7 2
1 1996 8 1
1 1996 11 4
1 1996 12 2
1 1996 13 3
1 1996 14 1
1 1996 15 1
1 1996 17 1
1 1996 19 1
1 1996 21 5
1 1996 22 2
1 1996 23 1
1 1996 26 1
1 1996 30 4
1 1996 31 1
1 1996 32 2
1 1996 34 30
1 1996 35 3
1 1996 36 5
1 1996 37 1
1 1996 40 1
1 1996 41 3
1 1996 42 2
1 1996 43 1
1 1996 44 18
1 1996 45 4
1 1996 47 2
1 1996 48 1
1 1997 3 2
1 1997 6 1
1 1997 7 3
1 1997 9 1
1 1997 10 1
1 1997 11 6
1 1997 12 3
1 1997 13 4
1 1997 17 1
1 1997 18 2
1 1997 19 2
1 1997 20 2
1 1997 21 3
1 1997 22 1
1 1997 23 2
1 1997 28 1
1 1997 29 1
1 1997 30 2
1 1997 31 4
1 1997 33 1
1 1997 34 21
1 1997 35 3
1 1997 36 6
1 1997 37 2
1 1997 41 5
1 1997 42 3
1 1997 43 3
1 1997 44 15
1 1997 45 3
1 1997 46 1
1 1997 47 5
1 1997 48 5
1 1998 2 4
1 1998 10 1
1 1998 11 2
1 1998 14 1
1 1998 18 1
1 1998 19 3
1 1998 21 5
1 1998 26 1
1 1998 30 3
1 1998 31 1
1 1998 32 9
1 1998 33 1
1 1998 34 13
1 1998 35 5
1 1998 36 5
1 1998 41 6
1 1998 42 2
1 1998 44 21
1 1998 45 1
1 1998 47 7
1 1998 48 1
1 1999 6 1
1 1999 8 1
1 1999 10 1
1 1999 11 3
1 1999 13 4
1 1999 14 3
1 1999 17 2
1 1999 18 1
1 1999 21 1
1 1999 23 2
1 1999 30 2
1 1999 31 1
1 1999 32 2
1 1999 33 1
1 1999 34 18
1 1999 35 2
1 1999 36 4
1 1999 37 1
1 1999 41 2
1 1999 43 2
1 1999 44 13
1 1999 47 3
1 1999 48 2
1 2000 2 1
1 2000 6 3
1 2000 7 3
1 2000 12 2
1 2000 13 1
1 2000 17 1
1 2000 18 1
1 2000 20 2
1 2000 21 2
1 2000 31 4
1 2000 32 4
1 2000 34 39
1 2000 35 4
1 2000 36 10
1 2000 37 1
1 2000 38 1
1 2000 40 1
1 2000 41 2
1 2000 42 6
1 2000 43 1
1 2000 44 9
1 2000 45 4
1 2000 47 11
1 2001 9 2
1 2001 10 1
1 2001 13 2
1 2001 15 2
1 2001 19 1
1 2001 21 1
1 2001 23 1
1 2001 30 7
1 2001 31 1
1 2001 32 6
1 2001 33 1
1 2001 34 18
1 2001 35 2
1 2001 36 6
1 2001 40 4
1 2001 41 2
1 2001 44 7
1 2001 45 5
1 2001 47 3
1 2001 48 1
1 2002 11 2
1 2002 13 2
1 2002 18 3
1 2002 30 1
1 2002 32 2
1 2002 33 1
1 2002 34 10
1 2002 35 3
1 2002 36 5
1 2002 42 3
1 2002 44 4
1 2002 47 9
1 2003 3 1
1 2003 12 1
1 2003 13 1
1 2003 17 1
1 2003 21 2
1 2003 30 1
1 2003 32 1
1 2003 33 1
1 2003 34 12
1 2003 35 3
1 2003 36 1
1 2003 37 2
1 2003 39 1
1 2003 42 1
1 2003 44 7
1 2003 45 3
1 2003 47 7
1 2004 7 2
1 2004 10 1
1 2004 13 3
1 2004 17 2
1 2004 18 2
1 2004 21 1
1 2004 23 1
1 2004 30 2
1 2004 31 1
1 2004 32 1
1 2004 34 13
1 2004 35 3
1 2004 37 1
1 2004 41 2
1 2004 44 14
1 2004 45 3
1 2004 47 5
1 2005 1
1 2005 7 1
1 2005 8 1
1 2005 9 2
1 2005 10 1
1 2005 11 1
1 2005 13 5
1 2005 14 1
1 2005 17 2
1 2005 18 1
1 2005 19 1
1 2005 21 3
1 2005 22 1
1 2005 30 3
1 2005 32 3
1 2005 33 2
1 2005 34 18
1 2005 35 5
1 2005 36 1
1 2005 37 2
1 2005 41 1
1 2005 42 2
1 2005 44 7
1 2005 46 2
1 2005 47 8
1 2006 7 1
1 2006 10 1
1 2006 12 1
1 2006 13 3
1 2006 17 1
1 2006 18 1
1 2006 21 1
1 2006 27 1
1 2006 28 1
1 2006 30 3
1 2006 32 2
1 2006 34 7
1 2006 35 5
1 2006 36 2
1 2006 37 1
1 2006 40 1
1 2006 41 3
1 2006 42 2
1 2006 43 1
1 2006 44 7
1 2006 45 1
1 2006 47 6
1 2006 48 2
1 2007 4 1
1 2007 8 1
1 2007 9 1
1 2007 12 4
1 2007 13 3
1 2007 14 1
1 2007 21 3
1 2007 22 1
1 2007 24 2
1 2007 27 2
1 2007 30 6
1 2007 31 1
1 2007 32 2
1 2007 33 1
1 2007 34 9
1 2007 36 2
1 2007 40 3
1 2007 42 2
1 2007 43 1
1 2007 44 12
1 2007 45 1
1 2007 47 6
1 2008 1
1 2008 6 1
1 2008 8 1
1 2008 10 1
1 2008 11 2
1 2008 13 2
1 2008 19 1
1 2008 21 3
1 2008 23 1
1 2008 27 1
1 2008 29 1
1 2008 30 3
1 2008 32 2
1 2008 33 2
1 2008 34 7
1 2008 35 1
1 2008 36 2
1 2008 38 1
1 2008 44 4
1 2008 45 2
1 2008 47 14
1 2009 1
1 2009 3 1
1 2009 7 1
1 2009 13 8
1 2009 18 1
1 2009 21 1
1 2009 23 1
1 2009 24 1
1 2009 27 2
1 2009 28 1
1 2009 30 2
1 2009 31 1
1 2009 34 10
1 2009 35 1
1 2009 36 1
1 2009 43 1
1 2009 44 1
1 2009 45 1
1 2009 47 3
1 2010 9 2
1 2010 13 1
1 2010 14 1
1 2010 28 2
1 2010 30 1
1 2010 31 1
1 2010 32 1
1 2010 34 6
1 2010 35 1
1 2010 36 4
1 2010 41 1
1 2010 44 1
1 2010 45 1
1 2011 2 1
1 2011 5 1
1 2011 7 1
1 2011 11 3
1 2011 12 1
1 2011 13 3
1 2011 17 1
1 2011 18 3
1 2011 21 2
1 2011 29 1
1 2011 30 2
1 2011 31 1
1 2011 32 2
1 2011 33 1
1 2011 34 4
1 2011 35 1
1 2011 36 1
1 2011 37 1
1 2011 38 1
1 2011 41 1
1 2011 44 3
1 2011 45 1
1 2011 47 5
1 2012 13 1
1 2012 14 1
1 2012 19 1
1 2012 27 1
1 2012 28 1
1 2012 30 3
1 2012 32 3
1 2012 34 1
1 2012 42 1
1 2012 44 4
1 2012 47 4
1 2013 11 1
1 2013 13 2
1 2013 14 1
1 2013 31 1
1 2013 33 1
1 2013 34 7
1 2013 35 1
1 2013 36 1
1 2013 41 1
1 2013 44 5
1 2013 46 2
1 2013 47 7
1 2014 1
1 2014 5 1
1 2014 9 1
1 2014 12 2
1 2014 13 3
1 2014 18 1
1 2014 28 1
1 2014 30 1
1 2014 32 1
1 2014 33 1
1 2014 34 7
1 2014 38 2
1 2014 40 2
1 2014 41 1
1 2014 44 14
1 2014 45 2
1 2014 47 4
1 2015 3 1
1 2015 7 1
1 2015 9 2
1 2015 13 2
1 2015 21 1
1 2015 30 2
1 2015 31 1
1 2015 32 3
1 2015 34 7
1 2015 36 3
1 2015 38 1
1 2015 40 1
1 2015 41 1
1 2015 44 10
1 2015 47 4
1 2016 11 3
1 2016 13 1
1 2016 14 1
1 2016 18 1
1 2016 21 1
1 2016 31 1
1 2016 32 1
1 2016 34 4
1 2016 36 2
1 2016 37 3
1 2016 43 1
1 2016 44 11
1 2016 47 2
1 2017 10 1
1 2017 13 3
1 2017 21 1
1 2017 24 1
1 2017 30 1
1 2017 31 3
1 2017 32 1
1 2017 34 4
1 2017 35 2
1 2017 36 2
1 2017 37 2
1 2017 38 1
1 2017 40 1
1 2017 44 2
2 1980 23 1
2 1980 42 1
2 1981 2 4
2 1981 14 1
2 1981 19 1
2 1981 21 1
2 1981 34 1
2 1981 40 1
2 1981 44 4
2 1981 47 2
2 1981 48 1
2 1982 4 1
2 1982 6 1
2 1982 12 1
2 1982 13 1
2 1982 14 1
2 1982 17 1
2 1982 24 1
2 1982 30 2
2 1982 33 1
2 1982 34 1
2 1982 36 2
2 1982 37 1
2 1982 40 1
2 1982 42 2
2 1982 44 5
2 1982 45 1
2 1982 47 7
2 1983 9 2
2 1983 11 1
2 1983 13 1
2 1983 17 1
2 1983 18 1
2 1983 23 1
2 1983 27 1
2 1983 30 4
2 1983 32 1
2 1983 33 1
2 1983 36 3
2 1983 40 1
2 1983 41 1
2 1983 43 2
2 1983 44 5
2 1983 45 2
2 1983 47 2
2 1984 8 1
2 1984 11 2
2 1984 12 2
2 1984 14 1
2 1984 16 2
2 1984 17 1
2 1984 19 2
2 1984 21 2
2 1984 24 1
2 1984 30 3
2 1984 32 1
2 1984 33 1
2 1984 34 5
2 1984 35 1
2 1984 36 2
2 1984 37 1
2 1984 39 2
2 1984 40 1
2 1984 41 3
2 1984 42 3
2 1984 43 1
2 1984 44 16
2 1984 45 1
2 1984 47 2
2 1985 1 1
2 1985 9 2
2 1985 10 1
2 1985 27 2
2 1985 30 2
2 1985 34 1
2 1985 38 1
2 1985 44 4
2 1985 45 2
2 1985 47 1
2 1986 2 1
2 1986 7 1
2 1986 9 1
2 1986 12 1
2 1986 19 1
2 1986 30 2
2 1986 31 1
2 1986 35 1
2 1986 36 2
2 1986 40 2
2 1986 44 7
2 1987 12 1
2 1987 30 1
2 1987 32 1
2 1987 34 1
2 1987 35 4
2 1987 40 1
2 1987 43 1
2 1987 44 9
2 1987 45 1
2 1987 47 1
2 1988 2 2
2 1988 7 2
2 1988 10 1
2 1988 14 1
2 1988 17 1
2 1988 22 1
2 1988 30 1
2 1988 32 2
2 1988 34 3
2 1988 35 2
2 1988 37 2
2 1988 42 1
2 1988 43 1
2 1988 44 2
2 1989 1 1
2 1989 2 2
2 1989 7 1
2 1989 10 1
2 1989 11 1
2 1989 12 2
2 1989 13 1
2 1989 17 1
2 1989 21 1
2 1989 22 1
2 1989 27 1
2 1989 28 1
2 1989 30 1
2 1989 32 2
2 1989 34 1
2 1989 35 1
2 1989 36 1
2 1989 40 1
2 1989 44 6
2 1989 47 1
2 1990 2 2
2 1990 18 1
2 1990 30 1
2 1990 32 1
2 1990 35 3
2 1990 37 2
2 1990 44 4
2 1990 45 1
2 1990 48 1
2 1991 6 1
2 1991 8 1
2 1991 11 1
2 1991 21 1
2 1991 22 1
2 1991 29 1
2 1991 31 1
2 1991 32 2
2 1991 34 1
2 1991 41 2
2 1991 42 1
2 1991 44 2
2 1991 45 1
2 1991 46 1
2 1991 47 1
2 1992 1 1
2 1992 7 1
2 1992 11 5
2 1992 12 2
2 1992 16 1
2 1992 18 1
2 1992 22 1
2 1992 29 1
2 1992 31 1
2 1992 32 2
2 1992 33 1
2 1992 34 4
2 1992 35 1
2 1992 36 1
2 1992 37 2
2 1992 40 1
2 1992 41 2
2 1992 42 1
2 1992 44 12
2 1992 45 3
2 1992 47 1
2 1992 48 1
2 1993 2 3
2 1993 7 1
2 1993 8 2
2 1993 11 3
2 1993 12 2
2 1993 13 1
2 1993 20 1
2 1993 21 2
2 1993 22 1
2 1993 23 2
2 1993 30 1
2 1993 34 3
2 1993 35 2
2 1993 36 1
2 1993 40 1
2 1993 41 3
2 1993 43 1
2 1993 44 16
2 1993 47 5
2 1994 1
2 1994 2 1
2 1994 7 3
2 1994 10 1
2 1994 11 5
2 1994 12 1
2 1994 14 1
2 1994 16 1
2 1994 17 2
2 1994 18 1
2 1994 21 1
2 1994 23 1
2 1994 30 2
2 1994 31 1
2 1994 32 2
2 1994 34 5
2 1994 35 4
2 1994 37 1
2 1994 40 1
2 1994 41 3
2 1994 42 3
2 1994 43 2
2 1994 44 18
2 1994 45 1
2 1994 47 3
2 1994 48 2
2 1995 1 1
2 1995 6 2
2 1995 7 1
2 1995 9 1
2 1995 11 2
2 1995 12 2
2 1995 13 4
2 1995 14 1
2 1995 17 2
2 1995 18 1
2 1995 19 2
2 1995 21 3
2 1995 22 1
2 1995 23 1
2 1995 30 1
2 1995 31 1
2 1995 32 3
2 1995 34 6
2 1995 35 2
2 1995 36 1
2 1995 37 5
2 1995 40 1
2 1995 41 4
2 1995 42 2
2 1995 44 12
2 1995 45 5
2 1995 46 1
2 1995 47 6
2 1995 48 1
2 1996 1 2
2 1996 6 1
2 1996 7 2
2 1996 10 1
2 1996 11 3
2 1996 12 4
2 1996 13 1
2 1996 16 1
2 1996 17 1
2 1996 18 1
2 1996 19 1
2 1996 21 2
2 1996 23 1
2 1996 30 4
2 1996 31 1
2 1996 32 4
2 1996 33 1
2 1996 34 13
2 1996 35 3
2 1996 36 6
2 1996 37 2
2 1996 40 2
2 1996 41 3
2 1996 42 1
2 1996 43 3
2 1996 44 16
2 1996 45 5
2 1996 47 6
2 1996 48 3
2 1997 2 1
2 1997 6 1
2 1997 9 1
2 1997 11 3
2 1997 12 1
2 1997 13 3
2 1997 14 1
2 1997 17 1
2 1997 19 1
2 1997 21 5
2 1997 22 1
2 1997 24 1
2 1997 30 1
2 1997 32 5
2 1997 34 16
2 1997 35 7
2 1997 36 3
2 1997 38 1
2 1997 41 5
2 1997 42 3
2 1997 43 1
2 1997 44 22
2 1997 45 4
2 1997 47 5
2 1997 48 8
2 1998 2 1
2 1998 7 3
2 1998 9 2
2 1998 10 1
2 1998 11 4
2 1998 12 5
2 1998 13 2
2 1998 14 1
2 1998 15 1
2 1998 17 2
2 1998 18 2
2 1998 19 1
2 1998 21 4
2 1998 29 1
2 1998 30 1
2 1998 32 5
2 1998 33 1
2 1998 34 20
2 1998 35 5
2 1998 36 2
2 1998 37 1
2 1998 38 1
2 1998 41 6
2 1998 42 4
2 1998 43 1
2 1998 44 25
2 1998 45 2
2 1998 46 2
2 1998 47 2
2 1998 48 2
2 1999 2 4
2 1999 6 3
2 1999 7 2
2 1999 12 1
2 1999 13 4
2 1999 14 3
2 1999 17 1
2 1999 18 6
2 1999 20 1
2 1999 21 1
2 1999 24 2
2 1999 31 2
2 1999 32 4
2 1999 33 1
2 1999 34 17
2 1999 35 4
2 1999 36 3
2 1999 37 1
2 1999 40 2
2 1999 41 1
2 1999 42 3
2 1999 43 2
2 1999 44 17
2 1999 45 1
2 1999 46 2
2 1999 47 6
2 2000 2 1
2 2000 6 1
2 2000 7 3
2 2000 8 1
2 2000 11 1
2 2000 13 5
2 2000 14 2
2 2000 17 1
2 2000 18 1
2 2000 19 1
2 2000 21 2
2 2000 27 1
2 2000 30 2
2 2000 31 2
2 2000 32 9
2 2000 34 38
2 2000 35 3
2 2000 36 10
2 2000 37 1
2 2000 38 3
2 2000 40 1
2 2000 41 3
2 2000 42 3
2 2000 43 1
2 2000 44 14
2 2000 45 2
2 2000 47 8
2 2000 48 2
2 2001 11 2
2 2001 12 1
2 2001 13 1
2 2001 14 1
2 2001 21 1
2 2001 27 1
2 2001 30 2
2 2001 31 2
2 2001 32 2
2 2001 34 13
2 2001 35 5
2 2001 36 4
2 2001 37 2
2 2001 41 1
2 2001 42 2
2 2001 44 6
2 2001 45 2
2 2001 46 1
2 2001 47 8
2 2001 48 1
2 2002 2 1
2 2002 6 1
2 2002 8 1
2 2002 10 1
2 2002 11 2
2 2002 12 5
2 2002 13 3
2 2002 27 2
2 2002 30 2
2 2002 32 2
2 2002 34 12
2 2002 35 1
2 2002 36 3
2 2002 42 1
2 2002 44 6
2 2002 45 2
2 2002 47 7
2 2002 48 3
2 2003 1
2 2003 7 1
2 2003 10 1
2 2003 11 1
2 2003 13 5
2 2003 21 1
2 2003 28 1
2 2003 30 3
2 2003 34 9
2 2003 35 4
2 2003 36 3
2 2003 42 1
2 2003 44 3
2 2003 46 1
2 2003 47 6
2 2004 8 2
2 2004 9 1
2 2004 10 1
2 2004 11 1
2 2004 13 4
2 2004 14 1
2 2004 15 2
2 2004 17 2
2 2004 19 1
2 2004 23 1
2 2004 28 1
2 2004 30 3
2 2004 32 1
2 2004 34 8
2 2004 35 8
2 2004 36 5
2 2004 37 3
2 2004 40 1
2 2004 41 1
2 2004 42 2
2 2004 43 1
2 2004 44 8
2 2004 45 1
2 2004 46 1
2 2004 47 6
2 2005 7 3
2 2005 11 2
2 2005 12 3
2 2005 13 4
2 2005 14 1
2 2005 21 1
2 2005 28 1
2 2005 30 1
2 2005 31 1
2 2005 32 1
2 2005 34 17
2 2005 35 1
2 2005 36 2
2 2005 37 1
2 2005 40 4
2 2005 42 2
2 2005 44 7
2 2005 45 2
2 2005 47 8
2 2006 1
2 2006 2 1
2 2006 10 1
2 2006 13 2
2 2006 22 1
2 2006 24 1
2 2006 26 1
2 2006 30 1
2 2006 32 1
2 2006 34 15
2 2006 35 1
2 2006 36 2
2 2006 37 2
2 2006 42 2
2 2006 43 1
2 2006 44 7
2 2006 45 1
2 2006 47 5
2 2006 48 2
2 2007 8 1
2 2007 9 2
2 2007 11 3
2 2007 12 1
2 2007 13 2
2 2007 14 1
2 2007 16 1
2 2007 19 1
2 2007 21 2
2 2007 28 1
2 2007 30 2
2 2007 31 1
2 2007 32 2
2 2007 34 10
2 2007 35 3
2 2007 36 3
2 2007 37 1
2 2007 38 1
2 2007 42 2
2 2007 44 11
2 2007 47 7
2 2008 2 1
2 2008 3 1
2 2008 10 1
2 2008 11 2
2 2008 13 5
2 2008 14 1
2 2008 17 1
2 2008 19 1
2 2008 27 2
2 2008 30 1
2 2008 31 2
2 2008 32 3
2 2008 33 1
2 2008 34 10
2 2008 35 1
2 2008 36 3
2 2008 37 2
2 2008 42 2
2 2008 44 3
2 2008 45 1
2 2008 46 1
2 2008 47 12
2 2009 1 1
2 2009 7 1
2 2009 18 1
2 2009 20 1
2 2009 24 1
2 2009 33 1
2 2009 34 6
2 2009 36 1
2 2009 37 1
2 2009 43 1
2 2009 44 1
2 2009 47 2
2 2010 7 1
2 2010 12 1
2 2010 14 2
2 2010 22 1
2 2010 30 3
2 2010 31 1
2 2010 34 10
2 2010 35 3
2 2010 36 2
2 2010 42 2
2 2010 44 1
2 2010 47 3
2 2011 10 1
2 2011 11 2
2 2011 13 1
2 2011 18 1
2 2011 27 1
2 2011 30 3
2 2011 32 4
2 2011 34 6
2 2011 36 1
2 2011 37 1
2 2011 40 1
2 2011 42 2
2 2011 44 1
2 2011 46 1
2 2011 47 8
2 2011 48 1
2 2012 8 1
2 2012 12 2
2 2012 13 1
2 2012 14 1
2 2012 30 4
2 2012 31 2
2 2012 32 1
2 2012 33 2
2 2012 34 10
2 2012 35 1
2 2012 36 2
2 2012 37 1
2 2012 40 2
2 2012 41 2
2 2012 42 1
2 2012 44 3
2 2012 47 4
2 2013 2 1
2 2013 7 1
2 2013 9 1
2 2013 13 2
2 2013 15 1
2 2013 18 1
2 2013 22 1
2 2013 30 2
2 2013 32 1
2 2013 34 5
2 2013 40 1
2 2013 41 2
2 2013 42 1
2 2013 44 5
2 2013 47 3
2 2014 10 1
2 2014 11 3
2 2014 12 1
2 2014 13 2
2 2014 14 2
2 2014 15 1
2 2014 27 1
2 2014 28 1
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10 1999 18 1
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10 1999 24 1
10 1999 28 1
10 1999 30 3
10 1999 31 2
10 1999 32 4
10 1999 34 32
10 1999 35 3
10 1999 36 6
10 1999 37 2
10 1999 39 1
10 1999 40 2
10 1999 42 1
10 1999 44 9
10 1999 45 1
10 1999 47 9
10 2000 2 1
10 2000 7 2
10 2000 8 1
10 2000 11 1
10 2000 12 4
10 2000 13 6
10 2000 17 1
10 2000 18 1
10 2000 21 2
10 2000 23 1
10 2000 24 1
10 2000 30 2
10 2000 31 1
10 2000 32 2
10 2000 33 1
10 2000 34 24
10 2000 35 8
10 2000 36 12
10 2000 37 5
10 2000 41 1
10 2000 42 3
10 2000 44 14
10 2000 45 2
10 2000 46 2
10 2000 47 9
10 2001 2 1
10 2001 3 1
10 2001 7 1
10 2001 10 1
10 2001 11 3
10 2001 12 1
10 2001 13 5
10 2001 18 2
10 2001 21 1
10 2001 27 1
10 2001 28 1
10 2001 30 2
10 2001 32 5
10 2001 34 13
10 2001 35 2
10 2001 36 4
10 2001 37 1
10 2001 40 3
10 2001 42 1
10 2001 43 1
10 2001 44 11
10 2001 45 1
10 2001 46 1
10 2001 47 6
10 2002 6 1
10 2002 9 2
10 2002 11 2
10 2002 12 1
10 2002 13 2
10 2002 30 2
10 2002 31 1
10 2002 34 11
10 2002 35 2
10 2002 36 4
10 2002 41 1
10 2002 44 5
10 2002 45 1
10 2002 47 5
10 2002 48 1
10 2003 6 1
10 2003 7 1
10 2003 13 2
10 2003 22 1
10 2003 23 1
10 2003 30 1
10 2003 31 3
10 2003 33 2
10 2003 34 10
10 2003 35 5
10 2003 36 3
10 2003 37 1
10 2003 42 2
10 2003 44 18
10 2003 45 3
10 2003 46 1
10 2003 47 5
10 2004 1 1
10 2004 4 1
10 2004 6 1
10 2004 7 1
10 2004 9 1
10 2004 11 2
10 2004 13 2
10 2004 17 1
10 2004 20 1
10 2004 21 1
10 2004 22 1
10 2004 24 1
10 2004 30 1
10 2004 32 3
10 2004 34 12
10 2004 35 1
10 2004 36 3
10 2004 44 9
10 2004 45 3
10 2004 46 1
10 2004 47 6
10 2005 7 1
10 2005 8 1
10 2005 11 5
10 2005 12 2
10 2005 19 1
10 2005 26 1
10 2005 30 2
10 2005 32 3
10 2005 34 12
10 2005 35 5
10 2005 36 3
10 2005 37 1
10 2005 40 1
10 2005 41 1
10 2005 42 1
10 2005 44 12
10 2005 45 3
10 2005 46 1
10 2005 47 10
10 2006 2 2
10 2006 4 1
10 2006 11 3
10 2006 12 1
10 2006 13 5
10 2006 23 3
10 2006 25 1
10 2006 32 5
10 2006 33 1
10 2006 34 18
10 2006 36 1
10 2006 37 1
10 2006 38 1
10 2006 40 1
10 2006 42 1
10 2006 44 9
10 2006 45 1
10 2006 46 1
10 2006 47 6
10 2006 48 2
10 2007 1
10 2007 1 1
10 2007 2 1
10 2007 9 1
10 2007 11 2
10 2007 12 1
10 2007 13 6
10 2007 15 1
10 2007 19 1
10 2007 21 2
10 2007 22 2
10 2007 23 2
10 2007 24 1
10 2007 30 1
10 2007 32 8
10 2007 33 3
10 2007 34 16
10 2007 35 1
10 2007 36 3
10 2007 37 4
10 2007 41 1
10 2007 43 1
10 2007 44 5
10 2007 45 2
10 2007 47 2
10 2008 1
10 2008 7 1
10 2008 11 1
10 2008 12 1
10 2008 13 4
10 2008 17 1
10 2008 18 1
10 2008 21 1
10 2008 24 1
10 2008 27 1
10 2008 30 2
10 2008 32 1
10 2008 34 8
10 2008 36 4
10 2008 44 2
10 2008 45 1
10 2008 47 1
10 2009 11 2
10 2009 12 1
10 2009 13 1
10 2009 18 1
10 2009 19 1
10 2009 28 1
10 2009 30 1
10 2009 32 1
10 2009 33 2
10 2009 34 7
10 2009 35 3
10 2009 36 2
10 2009 37 1
10 2009 41 2
10 2009 42 1
10 2009 47 6
10 2010 7 1
10 2010 13 2
10 2010 15 1
10 2010 17 1
10 2010 21 1
10 2010 30 2
10 2010 31 2
10 2010 32 2
10 2010 34 8
10 2010 35 2
10 2010 36 3
10 2010 42 1
10 2010 43 1
10 2010 44 5
10 2010 46 1
10 2010 47 2
10 2011 1 1
10 2011 7 1
10 2011 8 1
10 2011 14 1
10 2011 19 1
10 2011 23 1
10 2011 24 1
10 2011 28 1
10 2011 30 2
10 2011 31 1
10 2011 32 1
10 2011 34 5
10 2011 38 1
10 2011 41 1
10 2011 44 4
10 2011 46 1
10 2011 47 2
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10 2012 10 2
10 2012 12 2
10 2012 13 5
10 2012 14 1
10 2012 30 2
10 2012 31 1
10 2012 32 1
10 2012 34 5
10 2012 35 2
10 2012 41 4
10 2012 42 3
10 2012 44 8
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10 2012 47 2
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10 2013 13 2
10 2013 18 1
10 2013 21 2
10 2013 27 1
10 2013 30 1
10 2013 32 1
10 2013 34 7
10 2013 35 1
10 2013 36 1
10 2013 37 1
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10 2014 13 1
10 2014 14 1
10 2014 19 1
10 2014 21 1
10 2014 24 1
10 2014 27 1
10 2014 29 1
10 2014 30 1
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10 2014 32 1
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10 2014 36 1
10 2014 37 1
10 2014 40 2
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10 2015 21 2
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10 2015 27 2
10 2015 30 1
10 2015 31 1
10 2015 32 1
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10 2015 35 2
10 2015 36 1
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10 2015 38 1
10 2015 40 1
10 2015 41 1
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10 2015 47 2
10 2015 48 1
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10 2016 47 2
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11 1984 36 1
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11 1984 41 2
11 1984 42 2
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11 1988 41 1
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11 1989 21 1
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11 1989 40 1
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11 1990 21 1
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11 1990 30 1
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11 1990 47 1
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11 1991 12 1
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11 1991 20 1
11 1991 21 1
11 1991 22 1
11 1991 30 1
11 1991 31 1
11 1991 32 7
11 1991 34 4
11 1991 36 1
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11 1991 40 2
11 1991 41 1
11 1991 42 1
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11 1992 17 1
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11 1992 21 1
11 1992 30 1
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11 1992 32 1
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11 1992 35 1
11 1992 36 1
11 1992 37 1
11 1992 40 2
11 1992 41 1
11 1992 42 1
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11 1992 44 12
11 1992 45 3
11 1992 47 4
11 1993 4 1
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11 1993 10 1
11 1993 11 2
11 1993 12 1
11 1993 27 1
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11 1993 34 7
11 1993 36 1
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11 1993 40 1
11 1993 41 1
11 1993 43 1
11 1993 44 31
11 1993 45 1
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11 1994 13 1
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11 1994 20 1
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11 1994 22 1
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11 1994 32 3
11 1994 34 12
11 1994 35 3
11 1994 36 5
11 1994 38 1
11 1994 41 1
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11 1994 43 1
11 1994 44 23
11 1994 45 2
11 1994 46 1
11 1994 47 2
11 1994 48 1
11 1995 2 2
11 1995 9 2
11 1995 11 2
11 1995 12 4
11 1995 13 2
11 1995 14 2
11 1995 18 2
11 1995 19 1
11 1995 22 2
11 1995 27 1
11 1995 28 1
11 1995 30 3
11 1995 31 3
11 1995 32 3
11 1995 34 11
11 1995 35 1
11 1995 36 5
11 1995 37 1
11 1995 38 1
11 1995 40 4
11 1995 41 4
11 1995 42 2
11 1995 44 19
11 1995 45 2
11 1995 47 5
11 1995 48 3
11 1996 6 2
11 1996 7 2
11 1996 9 1
11 1996 11 2
11 1996 12 1
11 1996 19 1
11 1996 21 1
11 1996 22 1
11 1996 24 1
11 1996 31 2
11 1996 33 1
11 1996 34 12
11 1996 35 4
11 1996 36 5
11 1996 37 1
11 1996 40 2
11 1996 41 3
11 1996 42 2
11 1996 43 2
11 1996 44 18
11 1996 47 4
11 1996 48 2
11 1997 7 1
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11 1997 11 2
11 1997 12 2
11 1997 13 1
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11 1997 15 1
11 1997 17 1
11 1997 18 1
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11 1997 20 1
11 1997 21 1
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11 1997 24 1
11 1997 28 2
11 1997 30 2
11 1997 31 1
11 1997 32 6
11 1997 33 1
11 1997 34 20
11 1997 35 5
11 1997 36 4
11 1997 37 2
11 1997 38 2
11 1997 41 7
11 1997 42 3
11 1997 44 21
11 1997 45 2
11 1997 46 1
11 1997 47 8
11 1997 48 1
11 1998 1 1
11 1998 7 1
11 1998 10 1
11 1998 11 2
11 1998 12 3
11 1998 13 1
11 1998 14 2
11 1998 16 1
11 1998 17 1
11 1998 19 1
11 1998 21 3
11 1998 26 1
11 1998 28 1
11 1998 31 9
11 1998 32 4
11 1998 33 4
11 1998 34 16
11 1998 35 3
11 1998 36 3
11 1998 38 2
11 1998 41 2
11 1998 42 4
11 1998 43 2
11 1998 44 15
11 1998 45 3
11 1998 47 7
11 1998 48 3
11 1999 6 2
11 1999 7 1
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11 1999 12 3
11 1999 13 2
11 1999 14 1
11 1999 18 1
11 1999 19 2
11 1999 21 1
11 1999 24 2
11 1999 27 1
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11 1999 31 3
11 1999 32 6
11 1999 33 1
11 1999 34 23
11 1999 35 5
11 1999 36 6
11 1999 38 1
11 1999 42 1
11 1999 43 1
11 1999 44 10
11 1999 47 7
11 1999 48 1
11 2000 7 1
11 2000 8 1
11 2000 9 1
11 2000 11 1
11 2000 13 1
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11 2000 18 2
11 2000 19 1
11 2000 21 2
11 2000 30 2
11 2000 32 2
11 2000 33 1
11 2000 34 24
11 2000 35 7
11 2000 36 4
11 2000 37 3
11 2000 40 1
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11 2000 44 8
11 2000 45 2
11 2000 46 1
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11 2001 3 1
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11 2001 10 2
11 2001 11 2
11 2001 12 2
11 2001 13 3
11 2001 16 1
11 2001 21 1
11 2001 28 1
11 2001 30 1
11 2001 31 1
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11 2001 36 3
11 2001 37 1
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11 2001 45 1
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11 2002 3 1
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11 2002 11 1
11 2002 12 1
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11 2002 31 1
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11 2002 37 2
11 2002 43 1
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11 2002 45 2
11 2002 47 5
11 2003 2 1
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11 2003 7 1
11 2003 11 3
11 2003 12 2
11 2003 13 2
11 2003 18 1
11 2003 19 1
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11 2003 28 1
11 2003 31 1
11 2003 34 12
11 2003 35 3
11 2003 36 3
11 2003 40 1
11 2003 41 1
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11 2003 45 1
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11 2004 5 1
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11 2004 8 2
11 2004 10 1
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11 2004 41 1
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11 2004 43 1
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11 2005 37 1
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11 2006 7 1
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11 2007 40 1
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11 2008 36 1
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11 2009 2 1
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11 2009 17 1
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11 2009 24 1
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11 2009 41 1
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11 2010 13 1
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11 2010 19 1
11 2010 21 1
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11 2010 32 4
11 2010 34 8
11 2010 35 1
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11 2010 41 3
11 2010 42 1
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11 2011 37 1
11 2011 40 1
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11 2011 42 1
11 2011 43 1
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11 2011 45 1
11 2011 47 2
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11 2012 12 1
11 2012 14 1
11 2012 17 1
11 2012 19 1
11 2012 21 1
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11 2012 31 1
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11 2013 40 1
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11 2014 18 1
11 2014 21 1
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11 2014 32 1
11 2014 33 1
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11 2014 35 1
11 2014 36 1
11 2014 40 1
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11 2015 12 2
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11 2015 14 1
11 2015 17 3
11 2015 18 1
11 2015 24 1
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11 2015 40 1
11 2015 41 1
11 2015 42 2
11 2015 43 1
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12 1980 14 2
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12 1992 47 2
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12 1995 37 2
12 1995 41 6
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12 1995 44 19
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12 1996 38 2
12 1996 40 1
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12 1996 44 19
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12 1996 47 9
12 1996 48 1
12 1997 2 1
12 1997 6 1
12 1997 7 4
12 1997 11 7
12 1997 12 3
12 1997 13 2
12 1997 14 1
12 1997 17 1
12 1997 18 1
12 1997 19 1
12 1997 21 5
12 1997 22 1
12 1997 23 3
12 1997 28 1
12 1997 30 6
12 1997 31 2
12 1997 32 4
12 1997 34 14
12 1997 35 6
12 1997 36 2
12 1997 37 2
12 1997 38 1
12 1997 41 3
12 1997 42 2
12 1997 43 4
12 1997 44 34
12 1997 46 1
12 1997 47 14
12 1998 6 1
12 1998 8 1
12 1998 9 1
12 1998 10 1
12 1998 11 2
12 1998 12 1
12 1998 13 3
12 1998 14 1
12 1998 16 2
12 1998 17 1
12 1998 22 1
12 1998 23 1
12 1998 24 1
12 1998 30 5
12 1998 31 1
12 1998 32 4
12 1998 34 14
12 1998 35 5
12 1998 36 3
12 1998 38 1
12 1998 41 2
12 1998 42 2
12 1998 43 1
12 1998 44 11
12 1998 45 3
12 1998 47 6
12 1998 48 1
12 1999 2 1
12 1999 7 2
12 1999 13 1
12 1999 14 2
12 1999 17 1
12 1999 21 2
12 1999 23 1
12 1999 26 1
12 1999 30 2
12 1999 31 3
12 1999 32 5
12 1999 33 1
12 1999 34 40
12 1999 35 8
12 1999 36 8
12 1999 37 2
12 1999 40 1
12 1999 41 1
12 1999 42 3
12 1999 44 16
12 1999 45 2
12 1999 46 1
12 1999 47 7
12 2000 2 1
12 2000 3 1
12 2000 6 1
12 2000 7 1
12 2000 11 1
12 2000 12 1
12 2000 13 2
12 2000 21 1
12 2000 22 1
12 2000 28 1
12 2000 31 2
12 2000 32 2
12 2000 34 19
12 2000 35 7
12 2000 36 7
12 2000 37 3
12 2000 40 2
12 2000 41 2
12 2000 42 1
12 2000 44 11
12 2000 45 1
12 2000 46 1
12 2000 47 4
12 2000 48 3
12 2001 7 2
12 2001 11 1
12 2001 12 4
12 2001 13 3
12 2001 22 1
12 2001 30 1
12 2001 31 2
12 2001 32 5
12 2001 34 9
12 2001 35 3
12 2001 36 3
12 2001 37 1
12 2001 40 1
12 2001 43 1
12 2001 44 8
12 2001 46 1
12 2001 47 3
12 2002 1
12 2002 2 1
12 2002 3 1
12 2002 6 3
12 2002 8 1
12 2002 9 1
12 2002 11 1
12 2002 12 1
12 2002 13 1
12 2002 17 1
12 2002 18 1
12 2002 27 1
12 2002 30 1
12 2002 32 1
12 2002 34 12
12 2002 35 4
12 2002 36 2
12 2002 41 1
12 2002 43 2
12 2002 44 11
12 2002 45 7
12 2002 47 5
12 2003 6 1
12 2003 11 2
12 2003 13 5
12 2003 17 1
12 2003 21 1
12 2003 30 2
12 2003 31 2
12 2003 32 4
12 2003 33 1
12 2003 34 15
12 2003 35 6
12 2003 36 2
12 2003 37 1
12 2003 40 3
12 2003 43 1
12 2003 44 16
12 2003 45 2
12 2003 47 6
12 2004 2 1
12 2004 3 1
12 2004 8 1
12 2004 9 1
12 2004 10 1
12 2004 11 1
12 2004 12 4
12 2004 13 1
12 2004 14 2
12 2004 17 1
12 2004 19 1
12 2004 21 2
12 2004 22 1
12 2004 30 3
12 2004 32 4
12 2004 33 1
12 2004 34 12
12 2004 35 5
12 2004 36 5
12 2004 37 3
12 2004 40 1
12 2004 44 14
12 2004 45 1
12 2004 47 6
12 2005 7 1
12 2005 11 2
12 2005 12 2
12 2005 13 3
12 2005 30 1
12 2005 31 1
12 2005 32 3
12 2005 34 10
12 2005 35 5
12 2005 36 3
12 2005 38 1
12 2005 40 1
12 2005 41 1
12 2005 44 9
12 2005 45 3
12 2005 47 7
12 2006 1 1
12 2006 3 1
12 2006 9 1
12 2006 10 1
12 2006 11 2
12 2006 12 1
12 2006 13 3
12 2006 17 1
12 2006 18 1
12 2006 21 1
12 2006 26 1
12 2006 30 1
12 2006 32 1
12 2006 34 12
12 2006 36 4
12 2006 37 1
12 2006 38 1
12 2006 40 2
12 2006 44 11
12 2006 45 1
12 2006 47 4
12 2007 2 1
12 2007 7 1
12 2007 9 1
12 2007 11 1
12 2007 12 3
12 2007 13 3
12 2007 18 1
12 2007 21 4
12 2007 28 1
12 2007 30 1
12 2007 31 2
12 2007 32 3
12 2007 33 1
12 2007 34 6
12 2007 35 1
12 2007 36 6
12 2007 37 2
12 2007 41 2
12 2007 42 1
12 2007 43 1
12 2007 44 3
12 2007 46 1
12 2007 47 6
12 2008 1
12 2008 7 1
12 2008 11 1
12 2008 12 1
12 2008 13 1
12 2008 18 1
12 2008 21 2
12 2008 22 2
12 2008 24 1
12 2008 26 1
12 2008 32 1
12 2008 33 1
12 2008 34 11
12 2008 36 1
12 2008 41 1
12 2008 44 5
12 2008 45 2
12 2008 47 2
12 2009 8 1
12 2009 9 1
12 2009 12 2
12 2009 13 4
12 2009 14 2
12 2009 17 1
12 2009 19 1
12 2009 21 1
12 2009 22 1
12 2009 30 2
12 2009 32 2
12 2009 34 8
12 2009 36 2
12 2009 42 1
12 2009 43 1
12 2009 44 2
12 2009 46 1
12 2009 47 5
12 2009 48 1
12 2010 9 1
12 2010 12 1
12 2010 13 1
12 2010 17 1
12 2010 21 1
12 2010 22 2
12 2010 28 1
12 2010 30 1
12 2010 31 3
12 2010 32 2
12 2010 34 8
12 2010 35 5
12 2010 36 2
12 2010 37 1
12 2010 41 2
12 2010 42 1
12 2010 44 7
12 2010 45 1
12 2010 46 1
12 2010 47 5
12 2011 9 1
12 2011 12 3
12 2011 13 3
12 2011 19 2
12 2011 21 2
12 2011 22 1
12 2011 28 1
12 2011 30 1
12 2011 31 2
12 2011 32 1
12 2011 34 4
12 2011 35 1
12 2011 36 1
12 2011 40 1
12 2011 41 1
12 2011 43 1
12 2011 44 8
12 2011 47 6
12 2012 8 1
12 2012 10 2
12 2012 11 1
12 2012 13 3
12 2012 14 1
12 2012 17 1
12 2012 18 1
12 2012 20 1
12 2012 21 2
12 2012 22 1
12 2012 23 1
12 2012 24 1
12 2012 28 2
12 2012 30 1
12 2012 31 1
12 2012 34 6
12 2012 35 1
12 2012 36 1
12 2012 40 2
12 2012 41 3
12 2012 43 1
12 2012 44 3
12 2012 47 6
12 2012 48 1
12 2013 7 1
12 2013 12 2
12 2013 13 3
12 2013 14 1
12 2013 15 1
12 2013 24 1
12 2013 27 1
12 2013 28 1
12 2013 31 1
12 2013 32 3
12 2013 34 8
12 2013 35 3
12 2013 36 1
12 2013 41 3
12 2013 44 5
12 2013 45 2
12 2013 47 3
12 2014 1
12 2014 5 1
12 2014 11 1
12 2014 12 1
12 2014 13 2
12 2014 14 1
12 2014 19 1
12 2014 24 1
12 2014 27 1
12 2014 32 3
12 2014 34 10
12 2014 36 1
12 2014 38 1
12 2014 41 2
12 2014 42 1
12 2014 44 9
12 2014 45 1
12 2014 47 3
12 2015 6 1
12 2015 11 1
12 2015 13 4
12 2015 15 1
12 2015 30 2
12 2015 31 1
12 2015 34 7
12 2015 35 2
12 2015 36 1
12 2015 37 1
12 2015 39 1
12 2015 41 2
12 2015 44 8
12 2015 45 1
12 2015 47 4
12 2015 48 1
12 2016 2 1
12 2016 11 1
12 2016 12 3
12 2016 13 2
12 2016 17 1
12 2016 21 1
12 2016 22 1
12 2016 30 1
12 2016 34 7
12 2016 44 3
12 2016 47 2

Super User
Posts: 23,771

Re: Calculating wave of mergers

That's a lot of data, perhaps limit your example to a smaller subset.

Can you please include what  you've tried so far with regards to solving this problem?

Contributor
Posts: 73

Re: Calculating wave of mergers

Dear Ms. Reeza,

Nice to talking to you after long time. The steps I am following are given below:

1) I Split the data into 1980s, 1990s, 2000s and 2010s

2) I Calculate rolling 24 months moving total number of mergers by industry

3) I find out the highest 24-month concentration of merger bids involving firms in that industry in each decade

4) Taking the total number of bids over the entire decade for a given industry, I simulate 1000 distributions of that number of occurrences of industry member involvement in a bid over a 120-month period by randomly assigning each occurrence to a month where the probability of assignment is 1/120 for each month.

5) I then calculate the highest 24-month concentration of activity from each of the 1000 draws.

6) Finally, I compare the actual concentration of activity from the potential wave to the empirical distribution of 1000 peak 24-month concentrations. If the actual peak concentration exceeds the 95th percentile from that empirical distribution, that period is coded as a wave.

I have the announcement date of each mergers from 1978.

* I first keep announcement date and industry from the main database;

data wave;
set sdc;
keep __Date__Announced Aindus48;
run;

* I then calculate the number of mergers in each month by industry;

data wave; set wave; count=1; Month=month(__Date__Announced); Year=year(__Date__Announced); run;

proc sort data=wave; by Month Year; run;

proc freq data=wave;
tables Aindus48 / out=FreqCount sparse;
by Month Year;
weight Count;
run;

* I split the data Split the data into 1980s, 1990s, 2000s and 2010s;

Data wave_1980; set FreqCount; where 1979<year<1990; run; proc sort data=wave_1980; by year month; run;
Data wave_1990; set FreqCount; where 1989<year<2000; run; proc sort data=wave_1990; by year month; run;
Data wave_2000; set FreqCount; where 1999<year<2010; run; proc sort data=wave_2000; by year month; run;
Data wave_2010; set FreqCount; where 2009<year<2020; run; proc sort data=wave_2010; by year month; run;

Now I am trying to do the second step. Though I do not know I to calculate rolling total in SAS. The code also involves simulation. I do not know how to do it in SAS. I basically need your help in step 2 and 4.

Thank you for again being helpful

Super User
Posts: 23,771

Re: Calculating wave of mergers

Do you have SAS/ETS? If so, for #2, look at PROC EXPAND. Calculating rolling statistics is relatively easy:

https://gist.github.com/statgeek/27e23c015eae7953eff2

https://gist.github.com/statgeek/07a3708dee1225ceb9d4aa75daab2c52

For #4 consider PROC SURVEYSELECT and read David Cassell's paper - Don't be Loopy. It has code examples.

Contributor
Posts: 73

Re: Calculating wave of mergers

Dear Ms. Reeza,

Thank you for suggesting me the approcehes to solve the problem. Let me try them out and I will get back to you with the update. Once again thank you for being helpful.

Contributor
Posts: 73

Re: Calculating wave of mergers

Dear Ms. Reeza,

I calculated the 24 months rolling total and found highest 24-month concentration of merger bids using proc select. But taking the total number of bids over the entire decade for a given industry, I could not simulate 1000 distributions of that number of occurrences of industry member involvement in a bid over a 120-month period by randomly assigning each occurrence to a month where the probability of assignment is 1/120 for each month. I have included all the relevant codes.

* To calculate the 24 months rolling total and find highest 24-month concentration of merger bids;

proc sort data=wave_1980; by Aindus48 date; run;
proc timeseries data=wave_1980 out=wave_1980;
id date interval=month start='01Jan1980'd end='01Dec1989'd;
var COUNT;
by Aindus48;
run;

data wave_1980; set wave_1980; if COUNT=. then count1=0; else count1=count; drop count; rename count1=count; run;

proc expand data=wave_1980 out=wave_1980;
id date;
by Aindus48;
convert count = average_24 / method=none transformout= (movave 24);
run;

data wave_1980; set wave_1980; count_24=average_24*24; run;

data wave_1980; set wave_1980; count_24_1=round(count_24); drop count_24; rename count_24_1=count_24; run;

proc expand data=wave_1980 out=wave_1980 method = none;
by Aindus48;
id date;
convert date = date_lag24 / transformout=(lag 23);
run;

proc sort data=wave_1980 out=wave_1980;
by Aindus48 descending count_24;
run;

data wave_1980;
set wave_1980;
by Aindus48;
if first.Aindus48 then Con_A=1; * first member of the group then output;
drop average_24;
run;

* The code I tried to simulate the data (this code did not work);

proc surveyselect data=wave_1980 out=outboot
seed=30459584
method=urs samprate=1 outhits
rep=1000;
run;
sasfile wave_1980 close;
ods listing close;
proc sort data=outboot; by Aindus48 Replicate; run;
proc univariate data=outboot;
var count;
by Aindus48 Replicate;
output out=outall kurtosis=curt;
run;
ods listing;
proc univariate data=outall;
var curt;
output out=final pctlpts=2.5, 97.5 pctlpre=ci;
run;

Posts: 5,540

Re: Calculating wave of mergers

Interesting idea. As with simulation based tests in general, implementation requires attention to details.  Here is a permutation test that I tested with your data (the whole series):

``````data mergerCounts;
infile "&sasforum.\datasets\Calculating wave of mergers.txt" missover;
input Month Year Aindus48 COUNT;
month = mdy(month,1,year);
format month yymm7.;
drop year;
run;

proc sort data=mergerCounts; by Aindus48 month; run;

/* Add zero counts for missing months */
data fullMergerCounts;
do until(last.Aindus48);
set mergerCounts(rename=(month=xMonth count=xCount)); by Aindus48;
/* Assume records start in Jan of first mentioned year */
month = coalesce(month, mdy(12,1,year(xMonth)-1));
do while (month < intnx('month',xMonth,-1));
count = 0;
month = intnx("month", month,1);
output;
end;
month = xMonth;
count = coalesce(xCount, 0);
output;
end;
/* Complete last year until Dec */
do while (month < mdy(12, 1, year(xMonth)));
count = 0;
month = intnx("month", month,1);
output;
end;
format month yymm7.;
keep Aindus48 month count;
run;

/* Create random permutations of the merger series */
data simulMergerCounts;
call streamInit(2163453);
set fullMergerCounts;
output; /* Original counts will be identified with missing permNo */
do permNo = 1 to 99;
rnd = rand("uniform");
output;
end;
run;

proc sort data=simulMergerCounts; by Aindus48 permNo rnd month; run;

/* 24 months rolling sum of counts */
data mergerWaveCounts;
array a{24} _temporary_;
n = 0;
do until(last.permNo);
set simulMergerCounts; by Aindus48 permNo;
a{1+mod(n,24)} = count;
n = n + 1;
if n >= 24 then waveCount = sum(of a{*});
output;
end;
drop n;
run;

proc sql;
/* Find maximum number of mergers in 24 months in original data */
create table waveMax as
select
Aindus48,
max(waveCount) as observedMaxWave
from mergerWaveCounts
where permNo is missing
group by Aindus48;

/* Find maximum number of mergers in 24 months in randomly permuted series */
create table simulWaveMax as
select
Aindus48,
max(waveCount) as simulMaxWave
from mergerWaveCounts
where permNo is not missing
group by Aindus48, permNo;

/* Find position of observed maximums within maximums from permuted series */
create table waveStats as
select
a.Aindus48,
sum(a.observedMaxWave > b.simulMaxWave) as nSmallerWaveCounts,
count(b.simulMaxWave) as nSimulWaveCounts,
(1 + calculated nSmallerWaveCounts) / ( 1 + calculated nSimulWaveCounts) * 100 as wavePercentile
from
waveMax as a inner join
simulWaveMax as b on a.Aindus48=b.Aindus48
group by a.Aindus48;
quit;
``````
PG
Contributor
Posts: 73

Re: Calculating wave of mergers

Dear PGStats,

Thank you for helping me. I can see that you really worked hard to help me. I am grateful to you. Could you please include month column in the final file (wavestats)? Specifically I want to see beginning and ending month of the wave. Could you please tell me what nSmallerWaveCounts and nSimulWaveCounts indicate?

Posts: 5,540

Re: Calculating wave of mergers

nSmallerWaveCounts is the number of simulated random series with a maximum wave count smaller than the observed maximum wave

nSimulWaveCounts is the total number of simulated random series

To get the ending month of the maximum observed wave, modify the last step to:

``````
proc sql;
/* Find maximum number of mergers in 24 months in original data */
create table waveMax as
select
Aindus48,
max(waveCount) as observedMaxWave,
month
from mergerWaveCounts
where permNo is missing
group by Aindus48
having waveCount = max(waveCount);

/* Find maximum number of mergers in 24 months in randomly permuted series */
create table simulWaveMax as
select
Aindus48,
max(waveCount) as simulMaxWave
from mergerWaveCounts
where permNo is not missing
group by Aindus48, permNo;

/* Find position of observed maximums within maximums from permuted series */
create table waveStats as
select
a.Aindus48,
a.month as lastWaveMonth,
sum(a.observedMaxWave > b.simulMaxWave) as nSmallerWaveCounts,
count(b.simulMaxWave) as nSimulWaveCounts,
(1 + calculated nSmallerWaveCounts) / ( 1 + calculated nSimulWaveCounts) * 100 as wavePercentile
from
waveMax as a inner join
simulWaveMax as b on a.Aindus48=b.Aindus48
group by a.Aindus48, a.month;
quit;
``````

You will notice that there are many tied waves, which would indicate maximum waves that are shorter than 24 months.

PG
Contributor
Posts: 73

Re: Calculating wave of mergers

Dear

1) I have panel data for 48 industry wide monthly number of mergers data from 1978 to 2016. An industry may find 0 to any number of mergers in each month. I want to generate 1000 simulated distributions of the number of mergers in each month for each industry with the simulated total number of mergers in each industry equal to the original total number of mergers in that industry. Say, Airlines industry originally had total 200 mergers from 1978 to 2016. The each 1000 simulated distribution of the number of merges in airlines industry should have in total 200 mergers. I do not know what kind of distribution it would be (uniform, binomial etc). Most probably, it should uniform distribution. But all the simulated data should be integers.

2) Then I want to calculate the highest 24-month concentration of activity from each of the 1000 draws. For this I have to calculate the rolling 24 months total number of mergers in each industry in all the 1000 simulated distribution. Then I have to pick the month on which the total number of mergers is highest in each industry. So, I will get 1000 peak 24-month concentrations from 1000 simulated distributions for each industry.

3) Then I have to calculate 95th percentile from the distribution of 1000 peak 24-month concentrations

I need this 95th percentile of  the distribution of 1000 peak 24-month concentrations to compare with actual 24-month concentrations. The final data should have 95th percentile and the actual 24-month concentrations for 48 industries and the starting date of the actual 24-month concentrations.

Posts: 5,540

Re: Calculating wave of mergers

The code I gave you is a permutation test that doesn't assume a particular distribution. It uses the observed distribution of merger counts. Scaling up from 100 to 1000 replicates is straightforward but will require a lot of memory.

I can't do all the work for you. You should be able to take it from here.

Best of luck.

PG
Contributor
Posts: 73

Dear

Contributor
Posts: 73

Re: Calculating wave of mergers

Also if someone can give me the code to generate 1000 simulated distributions with the constraint- the total number of mergers in each industry in original file must equal to the number of mergers in each industry in all the 1000 distributions, I can do the rest of the work. Thank you in advance
Posts: 5,540

Re: Calculating wave of mergers

Note: My code does that, since it simply reorders the counts.

PG
Contributor
Posts: 73

Re: Calculating wave of mergers

Dear PG

I truly appreciate your help from my heart. But as you said that your code does a permutation test that doesn't assume a particular distribution. The specific journal I am following requires me to generate 1000 simulated uniform distributions. Could you please help me in generating 1000 simulated uniform distributions with the constraint- the total number of mergers in each industry in original file must equal to the number of mergers in each industry in all the 1000 distributions?

To be honest, I tried to generate the distributions by myself in the last 3 days but could not make it. I believe you know how to do it. I sorry I am bothering you a lot. If possible, please help me.

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