## # A tibble: 548 × 5
## # Groups:   symbol [4]
##    symbol date       price   change text                
##    <chr>  <date>     <dbl>    <dbl> <glue>              
##  1 GDPC1  1947-01-01 2034. NA       1947.1,
## Growth: NA   
##  2 GDPC1  1947-04-01 2029. -0.00267 1947.2,
## Growth: -0.3%
##  3 GDPC1  1947-07-01 2025. -0.00207 1947.3,
## Growth: -0.2%
##  4 GDPC1  1947-10-01 2057.  0.0156  1947.4,
## Growth: 1.6% 
##  5 GDPC1  1948-01-01 2087.  0.0150  1948.1,
## Growth: 1.5% 
##  6 GDPC1  1948-04-01 2122.  0.0165  1948.2,
## Growth: 1.7% 
##  7 GDPC1  1948-07-01 2134.  0.00573 1948.3,
## Growth: 0.6% 
##  8 GDPC1  1948-10-01 2136.  0.00112 1948.4,
## Growth: 0.1% 
##  9 GDPC1  1949-01-01 2107. -0.0138  1949.1,
## Growth: -1.4%
## 10 GDPC1  1949-04-01 2100. -0.00341 1949.2,
## Growth: -0.3%
## # … with 538 more rows

Analyze your client company’s data. Consider the following:

Timing Depth *Duration

of downturns in sale

Bank of New Hampshire

Timing The same increases and decreases in sales follow just after those of the overall economy.

Depth In most cases, the downturns are the same, if not even deeper than the overall economy.

Duration The increases in services is very similar in length compared to the overall economy, however the length of the decreases is significantly longer in most cases.