Analyzing the Impact of the Recession of 2008 on the Hospitality and Tourism Sector: A Cross-Over

Application of CAPM Theory

Sam G. Berry, DBA, Wesley M. Jones, Ph.D and Anthony A. Berkos Jr., MBA

The Citadel

INTRODUCTION

This paper provides an empirical review of the impact of the “Great Recession of 2008” on the growth and

volatility of employment in selected industry categories within the Hospitality and Tourism sector. The tools

for measuring the impacts are the Employment Beta, and the compound growth rate of employment in

selected North American Industry Classifications (NAIC’s) within the hospitality and tourism sector. The

employment beta (explained below) indexes the volatility of employment in an NAIC against the volatility of

employment in total non-farm employment. The source of the monthly employment data was the Bureau of

Labor Statistics’ (BLS) Employment, hours, and Earnings – National (Current Employment Statistics-CES)

employment data files. The NAIC's analyzed in this study were those in the hospitality sector that had

uninterrupted monthly data for the entire period of analysis. Data gaps and re-categorizing of employers

caused some industries' data to be unusable for this study. The monthly compounded growth rates in

employment for each NAIC were also calculated from the BLS employment data.

There were three time periods selected for study: (1), a Pre-Recession Period: January, 2002 – November,

2007 (2), a Recession Period: December, 2007 – June, 2009 and (3), a Post-Recession period; July, 2009 – May,

2013. There are also observations and measurements dealing with the total 2002 – 2013 time period. For

each time period, the volatility of employment was measured by NAIC employment betas, and the

employment growth was measured by the NAIC’s compound growth rates in employment for the designated

time periods. The desirable pattern in growth and volatility for an NAIC was for it to exhibit sustained

employment growth and a low employment beta. The growth and volatility patterns for each NAIC studied

are displayed in tables to follow.

DEVELOPING THE EMPLOYMENT BETA

The Employment Beta is built upon logic very similar to the well-known Common Stock Beta originally

developed by William F. Sharpe, in his Capital Asset Pricing Model (CAPM). Sharpe’s common stock beta

Employment Beta page 2

measured the volatility of return in an individual stock relative to the volatility of return in the overall

common stock market, as represented by a major stock market index (Standard and Poor’s 500 Stock Index, or

the New York Stock Exchange Composite Index). In brief, If a stock’s volatility matched that of the overall

market, its Beta Coefficient was 1.0. If the stock was more volatile than the market, its beta would be >1.0;

less volatility than the market would result in a beta of <1.0. Aggressive investors would generally prefer

higher-beta stocks, and conservative investors would prefer lower-beta stocks. Sharpe’s models of stock price

volatility, systematic and non-systematic risk assessment, and portfolio construction became widely employed

in the 1970’s and remains wide use today. Dr. Sharpe was awarded the Nobel Prize in Economics in 1990 for

his body of work in capital asset pricing.

The Methodology

To develop the Employment Beta, the monthly percentage change in employment in an NAIC was regressed

against the monthly percentage change in Total Non-Farm Employment. In the resulting simple linear

equation, %∆NAIC = a + (BNAIC) (%∆NonFarm) , the coefficient on the independent term %∆NonFarm is the

Employment Beta. The regression results were then subjected to the customary statistical evaluations done

on volatility- beta type research, where the primary emphasis is on evaluating the statistical significance of the

beta coefficient.

The Calculated Beta’s

The resulting employment betas that were statistically acceptable for use in our analyses are shown in Table 1:

Employment Betas by NAIC: Pre, Post and Full Sample Betas. The * symbols by the p-values indicate: 3-star,

***: <1.0%, 2-stars, **: >1.0, but <5%, and 1-star, *: >5%, but <10%. Using NAIC 481, Air Transportation, as

an example, The NAIC 481 employment beta for the pre-recession period was .272, with a standard error of

0.1251, and a p-value of .0331. The post-recession and full-sample columns are constructed in the same

manner.

There are 27 NAIC’s appearing in Table 1. Fifteen of the NAIC’s shown in the table had statistically usable

beta’s for the pre-recession period, 15 NAIC’s had usable beta’s for the post-recession period, and 19 had

usable beta’s for the full sample time period.

place Table I about here, page 3

Employment Beta page 4

The Calculated Growth Rates

Recall that the annual compound growth rate in employment was also calculated for each of the NAIC’s

studied, for each period of analysis. Each NAIC employment beta and employment growth rate were

combined and then grouped into the following growth/volatility groupings.

RESULTS: EMPLOYMENT GROWTH/ EMPLOYMENT BETA GROUPINGS

Pre-Recession Results

The groupings displayed below were summarized from the Pre-Recession analysis results. Combinations of

growth rate and employment betas were grouped in order of employment growth and volatility, with the High

Growth/ Low Beta (upper right corner, Pre-Recession Groupings) exhibiting the strongest growth during the

period and also the lowest employment volatility as indicated by their employment beta. The “high beta”

designation is given to those NAIC’s with a beta > 1.0; “low beta” denotes a beta < 1.0. “High growth” is

interpreted as a growth rate in excess of .933 which is the overall growth rate for total non-farm employment

for the period being analyzed; “low growth” is less than .933. These High Growth NAIC’s (upper right box)

were leading the hospitality and Tourism sector during this time period, with statistically significant results.

Other NAIC’s may have shown employment growth and/or less employment volatility, but their measures

were statistically unreliable. The remaining groupings exhibit downward degrees of growth and volatility

characteristics. The High Growth/High Beta group (lower right) did provide high employment growth, but also

exhibited high volatility of employment as shown by the high beta’s. The next group, Low Growth/Low Beta,

(upper left) exhibited low growth, but at least some positive growth, with an acceptable beta. Then decline

starts, with the Negative Growth/Low beta group being a “stably declining NAIC”. And lastly, the NAIC 4453

(Beer, Wine and Liquor Stores) and NAIC 7131 (Amusement Parks and Arcades) suffered employment declines

and slightly higher employment volatility. The serious decline in amusement park employment was a well

noted negative impact of the 2008 "Great Recession".

place Exhibit 1: Pre-Post Recession Groupings about here, page 5

Employment Beta Page 6

Post-Recession Results

The severity of the 2008 recession becomes strikingly evident when reviewing the post-recession employment

betas and employment growth rates. Employment growth rates of 4 and 5% coupled with low employment

betas (less than 1.0) were seen during the pre-recession period (upper right box of pre-recession grouping). In

the post-recession groupings, only one NAIC exhibited the desirable combination of higher growth and low

beta: NAIC 482, Rail Transportation. The post-recession employment growth rate for total non-farm

employment was 1.218. Another five NAIC's had high employment growth, but their growth was combined

with high employment betas - - high employment volatility. (These NAIC's appear on the right side of the Post-

Recession Groupings Categories.) On the left side of the Post-Recession Groupings it can be seen that the

desirable low beta measures are paired off with low employment growth. Lastly, there are 4 high beta

industries exhibiting low employment growth - - the worst pairing of growth and volatility characteristics. In

the pre-recession period, there were only two of the less desirable industries. Another notable difference

between the Pre and Post recessionary periods is that there were 9 growing NAIC's in the Pre-Recession

period; but only 4 growing NAIC's in the Post-Recession period.

SUMMARY AND CONCLUSIONS

Using an adaptation of the well-known Capital Asset Pricing Model, this analysis has drawn employment data

from statistics compiled by the U.S. Bureau of Labor Statistics to analyze the growth/declines and the volatility

of employment changes in the Hospitality and Tourism sector. The impact on the sector was measured in

both employment growth and volatility terms. The level and volatility of employment in 27 NAIC Categories of

employers in the Hospitality and Tourism industry were analyzed in a manner similar the analysis of common

stocks. The NAIC's per cent change in monthly employment was regressed against total non-farm

employment in the US, providing an Employment Beta analogous to the common stock beta's first calculated

by William F. Sharpe. Employment Beta's greater than 1.0 indicate a higher degree of employment volatility in

the NAIC. The compound growth rate in monthly employment was also calculated for each NAIC. Using the

two characteristics , industry growth and volatility pairings permitted construction of growth/volatility

Employment Beta Page 7

industry groupings to assess the relative employment strengths and staying power in the Hospitality and

Tourism sector. This research confirms that the 2008 recession left major, slow-healing scars on the Hospitality

and Tourism sector. Stable employment growth is only now returning to the sector, six years later.

Developers and regional planners are offered the Employment Beta developed here to enable them to better

assess the potentials of selected categories of employers in the Hospitality and Tourism sector. Regional

economics and regional planning students preparing themselves to study the hospitality industry will also

benefit by studying this "cross-over" application of the Capital Asset Pricing Model, the Employment Beta.