How to interpolate data set with by statement

[KRA15]

proc expand data=interpoled_dataout=interpoled_data from=year;
	by cluster;
	id year2; 
		convert emp / method=join;  
run;

I have two data points for two years (1990 and 2018) for three clusters:

year1	cluster	emp
01JAN1990	Accommodation and Food Svcs	12868
01JAN2018	Accommodation and Food Svcs	31869.5
01JAN1990	Advanced Materials	7477.417
01JAN2018	Advanced Materials	3339.25
01JAN1990	Agribusiness	5567.5
01JAN2018	Agribusiness	3619.5

I want to interpolate the data for each cluster from 1990 - 2018, (i.e. 1990, 1991, 1992, ...., 2018) for each cluster, such that:

Accommodation and Food Svcs 1990 emp

Accommodation and Food Svcs 1991 emp = 1990 emp + (2018 emp - 1990 emp) / 29 years

.

.

.

Accommodation and Food Svcs 2017 emp = 2016 emp + (2018 emp - 1990 emp) / 29 years

Accommodation and Food Svcs 2018 emp

Advance Materials 1990 emp

Advance Materials 1991 emp = 1990 emp + (2018 emp - 1990 emp) / 29 years

.

.

.

Advance Materials 2017 emp = 2016 emp + (2018 emp - 1990 emp) / 29 years

Advance Materials 2018 emp

Agribusiness 1990 emp

Agribusiness 1991 emp = 1990 emp + (2018 emp - 1990 emp) / 29 years

.

.

.

Agribusiness 2017 emp = 2016 emp + (2018 emp - 1990 emp) / 29 years

Agribusiness 2018 emp

Desired result:

year1	cluster	emp
01JAN1990	Accommodation and Food Svcs	12868
01JAN1991	Accommodation and Food Svcs	13523.22
01JAN1992	Accommodation and Food Svcs	14178.45
01JAN1993	Accommodation and Food Svcs	14833.67
01JAN1994	Accommodation and Food Svcs	15488.9
01JAN1995	Accommodation and Food Svcs	16144.12
01JAN1996	Accommodation and Food Svcs	16799.34
01JAN1997	Accommodation and Food Svcs	17454.57
01JAN1998	Accommodation and Food Svcs	18109.79
01JAN1999	Accommodation and Food Svcs	18765.02
01JAN2000	Accommodation and Food Svcs	19420.24
01JAN2001	Accommodation and Food Svcs	20075.47
01JAN2002	Accommodation and Food Svcs	20730.69
01JAN2003	Accommodation and Food Svcs	21385.91
01JAN2004	Accommodation and Food Svcs	22041.14
01JAN2005	Accommodation and Food Svcs	22696.36
01JAN2006	Accommodation and Food Svcs	23351.59
01JAN2007	Accommodation and Food Svcs	24006.81
01JAN2008	Accommodation and Food Svcs	24662.03
01JAN2009	Accommodation and Food Svcs	25317.26
01JAN2010	Accommodation and Food Svcs	25972.48
01JAN2011	Accommodation and Food Svcs	26627.71
01JAN2012	Accommodation and Food Svcs	27282.93
01JAN2013	Accommodation and Food Svcs	27938.16
01JAN2014	Accommodation and Food Svcs	28593.38
01JAN2015	Accommodation and Food Svcs	29248.6
01JAN2016	Accommodation and Food Svcs	29903.83
01JAN2017	Accommodation and Food Svcs	30559.05
01JAN2018	Accommodation and Food Svcs	31869.5
01JAN1990	Advanced Materials	7477.417
01JAN1991	Advanced Materials	7334.721
01JAN1992	Advanced Materials	7192.026
01JAN1993	Advanced Materials	7049.33
01JAN1994	Advanced Materials	6906.635
01JAN1995	Advanced Materials	6763.94
01JAN1996	Advanced Materials	6621.244
01JAN1997	Advanced Materials	6478.549
01JAN1998	Advanced Materials	6335.853
01JAN1999	Advanced Materials	6193.158
01JAN2000	Advanced Materials	6050.463
01JAN2001	Advanced Materials	5907.767
01JAN2002	Advanced Materials	5765.072
01JAN2003	Advanced Materials	5622.376
01JAN2004	Advanced Materials	5479.681
01JAN2005	Advanced Materials	5336.986
01JAN2006	Advanced Materials	5194.29
01JAN2007	Advanced Materials	5051.595
01JAN2008	Advanced Materials	4908.899
01JAN2009	Advanced Materials	4766.204
01JAN2010	Advanced Materials	4623.509
01JAN2011	Advanced Materials	4480.813
01JAN2012	Advanced Materials	4338.118
01JAN2013	Advanced Materials	4195.422
01JAN2014	Advanced Materials	4052.727
01JAN2015	Advanced Materials	3910.032
01JAN2016	Advanced Materials	3767.336
01JAN2017	Advanced Materials	3624.641
01JAN2018	Advanced Materials	3339.25
01JAN1990	Agribusiness	5567.5
01JAN1991	Agribusiness	5500.328
01JAN1992	Agribusiness	5433.155
01JAN1993	Agribusiness	5365.983
01JAN1994	Agribusiness	5298.81
01JAN1995	Agribusiness	5231.638
01JAN1996	Agribusiness	5164.466
01JAN1997	Agribusiness	5097.293
01JAN1998	Agribusiness	5030.121
01JAN1999	Agribusiness	4962.948
01JAN2000	Agribusiness	4895.776
01JAN2001	Agribusiness	4828.603
01JAN2002	Agribusiness	4761.431
01JAN2003	Agribusiness	4694.259
01JAN2004	Agribusiness	4627.086
01JAN2005	Agribusiness	4559.914
01JAN2006	Agribusiness	4492.741
01JAN2007	Agribusiness	4425.569
01JAN2008	Agribusiness	4358.397
01JAN2009	Agribusiness	4291.224
01JAN2010	Agribusiness	4224.052
01JAN2011	Agribusiness	4156.879
01JAN2012	Agribusiness	4089.707
01JAN2013	Agribusiness	4022.534
01JAN2014	Agribusiness	3955.362
01JAN2015	Agribusiness	3888.19
01JAN2016	Agribusiness	3821.017
01JAN2017	Agribusiness	3753.845
01JAN2018	Agribusiness	3619.5

[ChrisNZ]

1. Try reducing your problem into something more concise

2. Provide the data as a data step

3. Avoid attaching MS Office files