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40
average (all industries). These indicators provide the statewide average as a norm, or
benchmark, as an alternative to using the nation as a benchmark.
Many of the indicators will be measured in dollar units. To remove the effects of
inflation over time, it is recommended that the values of these indicators be transformed into
constant dollars using the consumer price index from the U.S. Bureau of Labor Statistics as the
deflator.
Section 2.3 Analytical Techniques and Models
In addition to the descriptive technique of graphing the indicators as time-series, several
simple techniques can provide insight into how particular clusters or core industries in North
Carolina are performing. Shift-share models provide easy-to-calculate tools that allows the
analyst to compare the performance of a North Carolina cluster (or core industry) over a chosen
temporal period against the nation. There are a family of shift-share models that have been
developed. Perhaps the most useful of these is the ‘classical’ shift-share. This particular model
decomposes change over the recent time period into national growth share, an industry-mix
component, and a regional shift component.
Eq. 1 (Si
t – Si
t-m) / Si
t-m = (NT
t – NT
t-m) / Ni
t-m
+ (Ni
t – Ni
t-m) / Ni
t-m – (NT
t – NT
t-m) / NT
t-m
+ (Si
t – Si
t-m) / Si
t-m – (Ni
t – Ni
t-m) / Ni
t-m
where S refers to the state level of a particular economic variable,
N refers to the national level,
i refers to a particular cluster or core industry,
T refers to total all industries,
t refers to the current year
t-m refers to m years earlier.
In this version of the shift-share model, the left-hand side and each of the components on the
right hand side of the identity are expressed as rates of change. If one multiplies each term in the
model by 100, the rates of change are converted to percent changes. Perhaps the most common
application of the classical shift-share model uses employment as the economic variable. Then
the model decomposes the state’s employment growth rate over the last m years in terms of the
performance of the national economy as a whole, the performance of the national cluster (or core
industry) in employment growth rate compared to the total national employment growth rate, and
finally the difference between the state’s employment growth rate for the cluster and the
nation’s. The so-called industry mix component yields information about whether the cluster or
core industry was an over-performer or under-performer at the national level, while the regional
shift component indicates whether the state’s cluster outperformed or underperformed the same
cluster at the national level. Under-performance for this last component implicitly indicates a
loss of competitive advantage over the time period. It should be clear, however, that shift-share
models are not explanatory; they do not provide explanations for under- or over-performance,
but instead indicate to the analyst where deeper investigation may be warranted.
Object Description
Description
| Title | Regional vision plan integration and implementation : phase II : final report - Page 46 |
| Full Text | 40 average (all industries). These indicators provide the statewide average as a norm, or benchmark, as an alternative to using the nation as a benchmark. Many of the indicators will be measured in dollar units. To remove the effects of inflation over time, it is recommended that the values of these indicators be transformed into constant dollars using the consumer price index from the U.S. Bureau of Labor Statistics as the deflator. Section 2.3 Analytical Techniques and Models In addition to the descriptive technique of graphing the indicators as time-series, several simple techniques can provide insight into how particular clusters or core industries in North Carolina are performing. Shift-share models provide easy-to-calculate tools that allows the analyst to compare the performance of a North Carolina cluster (or core industry) over a chosen temporal period against the nation. There are a family of shift-share models that have been developed. Perhaps the most useful of these is the ‘classical’ shift-share. This particular model decomposes change over the recent time period into national growth share, an industry-mix component, and a regional shift component. Eq. 1 (Si t – Si t-m) / Si t-m = (NT t – NT t-m) / Ni t-m + (Ni t – Ni t-m) / Ni t-m – (NT t – NT t-m) / NT t-m + (Si t – Si t-m) / Si t-m – (Ni t – Ni t-m) / Ni t-m where S refers to the state level of a particular economic variable, N refers to the national level, i refers to a particular cluster or core industry, T refers to total all industries, t refers to the current year t-m refers to m years earlier. In this version of the shift-share model, the left-hand side and each of the components on the right hand side of the identity are expressed as rates of change. If one multiplies each term in the model by 100, the rates of change are converted to percent changes. Perhaps the most common application of the classical shift-share model uses employment as the economic variable. Then the model decomposes the state’s employment growth rate over the last m years in terms of the performance of the national economy as a whole, the performance of the national cluster (or core industry) in employment growth rate compared to the total national employment growth rate, and finally the difference between the state’s employment growth rate for the cluster and the nation’s. The so-called industry mix component yields information about whether the cluster or core industry was an over-performer or under-performer at the national level, while the regional shift component indicates whether the state’s cluster outperformed or underperformed the same cluster at the national level. Under-performance for this last component implicitly indicates a loss of competitive advantage over the time period. It should be clear, however, that shift-share models are not explanatory; they do not provide explanations for under- or over-performance, but instead indicate to the analyst where deeper investigation may be warranted. |
