I am merging dataset #1 with the following structure:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str24 province float year long id byte job int yearstart
"anhui" 1951 13843 1 1943
"anhui" 1951 13844 1 1950
"anhui" 1951 13845 1 1946
"anhui" 1951 13852 1 1951
"anhui" 1951 13860 1 1947
"anhui" 1951 13867 1 1949
"anhui" 1951 13870 1 1947
"anhui" 1951 13886 1 1938
"anhui" 1951 13887 2 1950
"anhui" 1951 13887 3 1950
"anhui" 1951 13899 1 1950
"anhui" 1951 13902 1 1946
"anhui" 1951 13923 1 1948
"anhui" 1951 13968 2 1950
"anhui" 1951 13998 1 1950
"anhui" 1951 14013 1 1948
"anhui" 1951 14014 1 1948
"anhui" 1951 14038 1 1947
"anhui" 1951 14192 1 1950
"anhui" 1951 14197 1 1950
"anhui" 1951 14209 2 1949
"anhui" 1951 14209 3 1951
"anhui" 1951 14216 1 1951
"anhui" 1951 14241 1 1950
"anhui" 1951 14264 1 1948
"anhui" 1951 14265 1 1946
"anhui" 1951 14309 1 1948
"anhui" 1951 14310 1 1948
"anhui" 1951 14314 1 1943
"anhui" 1951 14336 1 1948
"anhui" 1951 14349 1 1949
"anhui" 1951 14362 1 1950
"anhui" 1951 14395 1 1945
"anhui" 1951 14401 1 1951
"anhui" 1951 14402 1 1951
"anhui" 1951 14530 1 1948
"anhui" 1951 14568 1 1948
"anhui" 1951 14568 2 1951
"anhui" 1951 14578 1 1946
"anhui" 1951 14611 1 1950
"anhui" 1951 14618 1 1942
"anhui" 1951 14624 1 1951
"anhui" 1951 14625 1 1950
"anhui" 1951 14630 1 1949
"anhui" 1951 14631 1 1948
"anhui" 1951 14634 1 1951
"anhui" 1951 14648 1 1944
"anhui" 1951 14703 1 1951
"anhui" 1951 14711 1 1951
"anhui" 1951     . .    .
"anhui" 1952 13746 1 1952
"anhui" 1952 13789 1 1952
"anhui" 1952 13843 1 1943
"anhui" 1952 13844 1 1950
"anhui" 1952 13845 1 1946
"anhui" 1952 13852 1 1951
"anhui" 1952 13860 1 1947
"anhui" 1952 13867 1 1949
"anhui" 1952 13870 1 1947
"anhui" 1952 13886 1 1938
"anhui" 1952 13886 2 1952
"anhui" 1952 13887 2 1950
"anhui" 1952 13887 3 1950
"anhui" 1952 13899 1 1950
"anhui" 1952 13902 1 1946
"anhui" 1952 13923 1 1948
"anhui" 1952 13968 2 1950
"anhui" 1952 13998 1 1950
"anhui" 1952 14013 1 1948
"anhui" 1952 14014 1 1948
"anhui" 1952 14038 1 1947
"anhui" 1952 14192 1 1950
"anhui" 1952 14197 1 1950
"anhui" 1952 14209 3 1951
"anhui" 1952 14214 1 1952
"anhui" 1952 14215 1 1952
"anhui" 1952 14216 1 1951
"anhui" 1952 14241 1 1950
"anhui" 1952 14264 1 1948
"anhui" 1952 14265 1 1946
"anhui" 1952 14309 1 1948
"anhui" 1952 14310 1 1948
"anhui" 1952 14314 1 1943
"anhui" 1952 14336 1 1948
"anhui" 1952 14349 1 1949
"anhui" 1952 14362 1 1950
"anhui" 1952 14395 1 1945
"anhui" 1952 14398 1 1952
"anhui" 1952 14401 1 1951
"anhui" 1952 14402 1 1951
"anhui" 1952 14409 1 1952
"anhui" 1952 14458 1 1952
"anhui" 1952 14530 1 1948
"anhui" 1952 14551 1 1952
"anhui" 1952 14568 1 1948
"anhui" 1952 14568 2 1951
"anhui" 1952 14577 1 1952
"anhui" 1952 14578 1 1946
"anhui" 1952 14578 2 1952
"anhui" 1952 14611 1 1950
end
label values id id
label def id 13746 "261676107002", modify
label def id 13789 "261676204001", modify
label def id 13843 "261676302001", modify
label def id 13844 "261676302002", modify
label def id 13845 "261676303001", modify
label def id 13852 "261676313002", modify
label def id 13860 "261676319001", modify
label def id 13867 "261676323002", modify
label def id 13870 "261676325001", modify
label def id 13886 "262728105001", modify
label def id 13887 "262728107002", modify
label def id 13899 "262728114002", modify
label def id 13902 "262728116001", modify
label def id 13923 "262728129001", modify
label def id 13968 "262728227001", modify
label def id 13998 "262728316002", modify
label def id 14013 "262728325001", modify
label def id 14014 "262728325002", modify
label def id 14038 "265359108002", modify
label def id 14192 "265359324001", modify
label def id 14197 "265359327001", modify
label def id 14209 "265576105001", modify
label def id 14214 "265576109001", modify
label def id 14215 "265576109002", modify
label def id 14216 "265576110001", modify
label def id 14241 "265576126002", modify
label def id 14264 "265576209001", modify
label def id 14265 "265576209002", modify
label def id 14309 "265576303001", modify
label def id 14310 "265576303002", modify
label def id 14314 "265576309001", modify
label def id 14336 "266059101001", modify
label def id 14349 "266059118001", modify
label def id 14362 "266059129002", modify
label def id 14395 "266059209001", modify
label def id 14398 "266059212002", modify
label def id 14401 "266059215001", modify
label def id 14402 "266059216001", modify
label def id 14409 "266059220001", modify
label def id 14458 "266059313002", modify
label def id 14530 "266306223002", modify
label def id 14551 "266306309001", modify
label def id 14568 "266306320002", modify
label def id 14577 "266306327001", modify
label def id 14578 "266306328001", modify
label def id 14611 "268606105001", modify
label def id 14618 "268606109001", modify
label def id 14624 "268606112002", modify
label def id 14625 "268606113002", modify
label def id 14630 "268606117001", modify
label def id 14631 "268606117002", modify
label def id 14634 "268606119002", modify
label def id 14648 "268606129001", modify
label def id 14703 "268606317001", modify
label def id 14711 "268606323001", modify
with dataset #2 with the following structure:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str24 province int year float(gdp_sec tenure)
"anhui"   1951       .        .
"anhui"   1952     2.3 6.246753
"anhui"   1953     2.9 6.246753
"anhui"   1954       3 6.246753
"anhui"   1955     3.7 6.246753
"anhui"   1956     4.6 6.246753
"anhui"   1957     6.4 6.246753
"anhui"   1958    13.6 6.246753
"anhui"   1959    19.7 6.246753
"anhui"   1960      23 6.246753
"anhui"   1961    11.2 6.246753
"anhui"   1962     7.9 6.246753
"anhui"   1963     8.7 6.246753
"anhui"   1964    11.3 6.246753
"anhui"   1965    14.5 6.246753
"anhui"   1966    17.1 6.246753
"anhui"   1967    12.1 6.246753
"anhui"   1968    11.3 6.142857
"anhui"   1969    15.7 6.142857
"anhui"   1970    20.5 6.142857
"anhui"   1971    24.8 6.246753
"anhui"   1972      26 6.246753
"anhui"   1973    28.4 6.246753
"anhui"   1974    25.9 6.246753
"anhui"   1975    29.2 6.246753
"anhui"   1976    31.4 6.246753
"anhui"   1977    34.7 6.246753
"anhui"   1978    40.6 6.246753
"anhui"   1979    44.8 6.246753
"anhui"   1980    50.1 6.246753
"anhui"   1981    52.5 6.246753
"anhui"   1982    59.7 6.246753
"anhui"   1983    73.2 6.246753
"anhui"   1984    92.8 6.246753
"anhui"   1985   117.9 6.246753
"anhui"   1986   137.6 6.246753
"anhui"   1987   157.8 6.246753
"anhui"   1988     201 6.246753
"anhui"   1989   227.8 6.246753
"anhui"   1990   251.5 6.246753
"anhui"   1991   280.3 6.246753
"anhui"   1992     333 6.246753
"anhui"   1993     445 6.246753
"anhui"   1994     542 6.246753
"anhui"   1995   660.1 6.246753
"anhui"   1996   742.1 6.246753
"anhui"   1997   828.9 6.246753
"anhui"   1998   920.5 6.246753
"anhui"   1999   974.3 6.246753
"anhui"   2000  1056.8 6.246753
"anhui"   2001  1254.9 6.246753
"anhui"   2002    1337 6.246753
"anhui"   2003  1535.3 6.246753
"anhui"   2004  1488.9 6.246753
"anhui"   2005 1837.36 6.246753
"anhui"   2006 2240.37 6.246753
"anhui"   2007    2810 6.246753
"anhui"   2008 3505.67 6.246753
"anhui"   2009 4064.72 6.246753
"anhui"   2010  5407.4 6.246753
"anhui"   2011    7062 6.246753
"anhui"   2012 8025.84 6.246753
"anhui"   2013 8880.45 6.246753
"anhui"   2014 9455.48 6.246753
"beijing" 1951    2.83 9.121951
"beijing" 1952    3.05 9.121951
"beijing" 1953    7.85 9.121951
"beijing" 1954    9.31 9.121951
"beijing" 1955   10.07 9.121951
"beijing" 1956   11.39 9.121951
"beijing" 1957   15.68 9.121951
"beijing" 1958   20.35 9.121951
"beijing" 1959   28.69 9.121951
"beijing" 1960   37.03 9.121951
"beijing" 1961   20.42 9.121951
"beijing" 1962    16.3 9.121951
"beijing" 1963   18.23 9.121951
"beijing" 1964   20.96 9.121951
"beijing" 1965    23.5 9.121951
"beijing" 1966   28.41 9.121951
"beijing" 1967   22.37 9.121951
"beijing" 1968   22.13 9.121951
"beijing" 1969    33.6 9.121951
"beijing" 1970   45.06 9.121951
"beijing" 1971   41.91 9.121951
"beijing" 1972   47.01 9.121951
"beijing" 1973   50.45 9.121951
"beijing" 1974   56.38 9.121951
"beijing" 1975    60.5 9.121951
"beijing" 1976   63.59 9.121951
"beijing" 1977   67.26 9.121951
"beijing" 1978   77.43 9.121951
"beijing" 1979   85.18 9.121951
"beijing" 1980   95.79 9.121951
"beijing" 1981   92.52 9.121951
"beijing" 1982   99.79 9.121951
"beijing" 1983  112.65 9.121951
"beijing" 1984  130.68 9.121951
"beijing" 1985  153.66 9.121951
"beijing" 1986  165.75 9.121951
end
Using the following code:

merge m:1 province year using "Industrial structure and political entrenchment.dta"

I got the following result:

Result # of obs.

not matched 10
from master 10 (_merge==1)
from using 0 (_merge==2)

matched 461,163 (_merge==3)

While I check on the observation numbers of the two variables from dataset #2 I only have observation numbers for the variable "gap_sec" 1940 and for the variable "tenure" 1837, the same numbers as in the second dataset. I had expected these two numbers are 461163 since the observation for the variable from dataset #2 in a province and year should have been matched each of the job held by each individual in that province and year.

Where did it go wrong?

Is my question clear enough?