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A simultaneous equations model of the hotel room supply and demand in Hong Kong
Hospitality Management 21 (2002) 455–462
Research note
A simultaneous equations model of the hotel room supply and demand in Hong Kong Hailin Qua,*, Peng Xub, Amy Tanc a
School of Hotel and Restaurant Administration, Oklahoma State University, 210 HESW, Stillwater, OK 74078, USA b Department of Economics, San Francisco State University, USA c School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong, SAR, China
Abstract The purpose of the study is to identify the important factors that influence the hotel room supply and demand, and their overall impact on the Hong Kong hotel industry. Nineteen years of time series data are used and a simultaneous equations econometric model is employed. The overall goodness-of-fit of both demand and supply models is very high, suggesting high predictive power. Empirical results indicate that ‘‘hotel room price’’ and ‘‘tourist arrivals’’ are significant factors driving the demand for hotel rooms. In addition, ‘‘1990–91 recession’’ and ‘‘the 1997–98 Asian financial crisis’’ had a significant negative impact on the demand for hotel rooms in Hong Kong. At the same time, ‘‘hotel room quantity demanded’’, ‘‘room occupancy rate’’, ‘‘last period’s room price’’, ‘‘labor cost’’, ‘‘last period’s average price of Grade A private offices’’, and ‘‘the Asian financial crisis’’ all have a significant impact on room price in the short run. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Supply and demand; Hong Kong hotel industry; Simultaneous equations
1. Introduction The imbalance between hotel room supply and demand in Hong Kong over the past 20 years or so has been a major concern of the Hong Kong hotel industry. Although lodging supply and demand in Hong Kong have grown at an annual average rate of 5.4 percent and 5.5 percent, respectively since 1980, such growths *Corresponding author. Tel.: +1-405-744-6711; fax: +1-405-744-6299. E-mail address: [email protected] (H. Qu). 0278-4319/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 8 - 4 3 1 9 ( 0 2 ) 0 0 0 3 1 - 2
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H. Qu et al. / Hospitality Management 21 (2002) 455–462
have by no means been steady. Between 1985 and 1989, for instance, average daily hotel room supply grew at a rapid annual average rate of 8.6 percent, while average daily room demand increased at an annual average rate of 6 percent only. However, the demand growth surged ahead of the supply growth between 1990 and 1998. During this period, daily room demand increased by 5.4 percent, whereas daily room supply grew only 3.5 percent. A wide range of factors, both internal and external to the industry, have led to the unbalanced growth between the supply and demand for lodging in Hong Kong. The recession episodes in the major outbound countries in the early 1970s, 80s, and 90s, for instance, have been cited as the main explanation for the decline in hotel room demand in Hong Kong during those periods. In addition, the political uncertainty in the early 80s and 90s precipitated by the pending reversion of Hong Kong to the mainland China, coupled with the Tiananmen Square incident in 1989, were also noted as the main causes of the fluctuating room demand in Hong Kong. More recently, the Asian financial crisis during the late 90s must also have had a negative impact on the Hong Kong hotel market. On the other hand, the conversion of some hotels into Grade A office buildings with appreciating real estate values was reported as the most prevalent influence of hotel room supply decrease in the last 4 years. In 1993 and 1994, for example, seven hotels with 3000 rooms in Hong Kong were demoted and redeveloped into office buildings. At the same time, only a couple of new hotels with a total of 400 rooms were introduced into the market (The Bank of East Asia Economic Research Department, 1995). Although this trend of hotels being redeveloped into more profitable office buildings has slowed, it has by no means ended. The purpose of this study is to identify the important factors that influence the hotel room supply and demand in Hong Kong, and their overall impact on Hong Kong hotel industry, by using a simultaneous equations econometric model. This study is undeniably useful to help government, hotel developers, and investors understand the determinants of supply and demand in the hotel industry, and to reliably forecast future supply of and demand for hotel rooms in Hong Kong.
2. Model description The data set used in this paper consists of time series data of 19 annual observations from 1980 to 1998, which were obtained from various governmental sources and trade publications in Hong Kong. Hiemstra’s and Ismail (1994) supply and demand model for the US lodging market serves as the theoretical basis for the study. Accordingly, the structural model of the Hong Kong hotel industry consists of the following four equations: Demand Qd ¼ f ðPr ; Z1 Þ;
ð1Þ
Short-run supply Pd ¼ f ðQd ; Qc ; Z2 Þ;
ð2Þ
Long-run supply Qs ¼ f ðPr ; Z3 Þ;
ð3Þ
Equilibrium condition Qc ¼ Qd =Os ;
ð4Þ
H. Qu et al. / Hospitality Management 21 (2002) 455–462
457
where Qd is the demand for hotel rooms, Pr is the room rate or price, Qs the long-run room supply or room capacity and Qc the room occupancy rate, defined as the ratio of Qd to Qs : Econometric implementation of the full theoretical model would involve estimating the structural Eqs. (1)–(3). Unfortunately, data limitations have prevented us from estimating Eq. (3) with reasonable degree of reliability in this study. Therefore, Eq. (3) cannot be estimated without sufficient data. The simultaneous equation system of Hong Kong hotel market demand and short-run supply is specified as follows: Demand QDt ¼ f ðPRt ; ARRt ; ERt ; INCt ; CPIt ; RECt ; CRSt Þ þ ut ;
ð5Þ
Short-run supply PRt ¼ f ðQDt ; QCt ; PRt1 ; LABt ; OFFt1 ; CRSt Þ þ vt ;
ð6Þ
where t is the time subscript, ut the stochastic error term of demand function, vt the stochastic error term of short-run supply function, QD the average number of rooms occupied per day (Hong Kong Monthly Digest of Statistics, 1980–1998), PR the average daily room rate in Hong Kong dollars (Hong Kong Tourist Association), ARR the annual number of tourist arrivals in Hong Kong (in thousands), ER the exchange rate, defined as trade-weighted value of the Hong Kong dollar versus the currencies of the G-10 countries: Australian Dollar, Canadian Dollar, Dutch Guilder, French Franc, German Mark, Italian Lira, Japanese Yen, Swiss Franc, UK Sterling, US Dollar (Hong Kong Monthly Digest of Statistics, 1980–1998), INC the median household income in Hong Kong dollars (Hong Kong Census and Statistics Department), CPI the Hong Kong’s Consumer Price Index (Hong Kong Census and Statistics Department), REC the dummy variable representing the effect of the 1990–1991 recession in some major outbound countries, QC the room occupancy rate (in percent), LAB the Cost of labor in thousands of Hong Kong dollars, defined as average monthly salaries including fringe benefits for all hotel employees (Hong Kong Quarterly Report of Wages, Salaries and Employee Benefits Statistics, 1980–1988), OFF the average square foot price of Grade A private offices in Hong Kong dollars (Hong Kong Property Review, 1980–1998) and CRS the dummy variable representing the effect of the Asian financial crisis in 1997 and 1998. Quantity demanded QD and room price PR are taken to be simultaneously determined within the system of Eqs. (5) and (6). Eq. (5) is a demand function, as such, QD and PR are expected to be inversely related, i.e. the coefficient of PR is expected to be negative. On the other hand, the relationship between PR and QD in the short-run supply Eq. (6) cannot be predicted priori and need to be empirically determined. As suggested by Fig. 1, on an annual basis, there has always been excess capacity (i.e. Qs > Qd ) in the hotel market during the sample period. Therefore, in principle, the hotel industry can fill their rooms up to capacity without having to use price as a rationing device, implying that PR and QD are not necessarily positively related. In fact, PR and QD may even be inversely related because, when faced with high excess room capacity in the short run, hotel operators may try to lower prices in order to sell more rooms (especially to tourists) by offering discounts and package
H. Qu et al. / Hospitality Management 21 (2002) 455–462
458 35,000 32,500 30,000 27,500 # of Rooms
Average Daily Room Supply
25,000 22,500 Average Daily Room Demand
20,000 17,500 15,000 12,500 10,000 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Year
Fig. 1. Hong Kong hotel room supply and demand, 1985–1998.
deals, etc., as incentives. Consequently, it is possible for the short-run supply curve to be slightly downward sloping. Some important factors believed to have impacted Hong Kong’s hotel industry are treated as the exogenous variables in demand equation (5). The variable ARR, or the annual number of tourist arrivals in Hong Kong, is included in the demand equation as a major demand shifter. Since more arrivals translate into higher demand for lodging, ARR is expected to have a positive effect on QD. The exchange rate variable ER is included in the demand model to capture the effect of the relative costs of traveling to and from Hong Kong. The effect of ER is expected to be negative—an appreciation of the Hong Kong dollar, or an increase in ER, makes it relatively more expensive for international travelers to visit Hong Kong. Following standard demand modeling practice, the median Hong Kong household income INC and prices of other goods and services, measured by CPI, are also included in the demand model. These variables could have an impact on the local demand generated by local residents. However, since the primary source of demand for lodging is not from local residents, these factors are not expected to have a very strong influence, if any, on demand. The dummy variable REC is included to capture the negative effect of the 1990–1991 recession in the major outbound countries including the United States. Finally, the dummy variable CRS is also included to capture the negative impact of the Asian financial crisis (in 1997 and 1998) on the Hong Kong hotel market. Some important exogenous factors are included in the short-run supply equation (6). Since room prices are not completely independent from period to period, it is suspected that PR lagged one period or room price prevailing in the previous period might have a positive influence on the current price PR. Hotel room occupancy rate
H. Qu et al. / Hospitality Management 21 (2002) 455–462
459
is expected to have a positive effect on room price. The labor cost variable LAB is expected to have a positive effect on price, as hoteliers are likely to pass higher labor costs on to hotel customers. In the long run, higher prices of Grade A private office space can lead to increased conversion of hotel rooms into office buildings and (hence) a reduction in hotel room supply. In the short run, while total hotel room supply is fixed, higher office prices can at least have some effect on hotel room prices. Therefore, OFF lagged one period or the previous period’s average price of Grade A offices in Hong Kong, is included as an exogenous variable. Finally, the dummy variable CRS is intended to capture the negative impact of the Asian financial crisis on hotel room price.
3. Results and discussion A linear specification of the supply and demand model, consisting of Eqs. (5) and (6), is estimated by using the two-stage least-squares estimator (2SLS). All of the exogenous variables of the system are used as instruments for the endogenous variables. Since the number of annual observations is relatively small, 2SLS is particularly attractive, as it is likely to have small-sample properties superior on most criteria to all other estimators. It is also fairly robust in that it is insensitive to other estimating problems such as multicollinearity and specification errors (Kennedy, 1992). The parameter estimates of the model are summarized in Table 1. The estimated demand equation has an adjusted R2 of 0.9964, indicating a very good fit. In other words, the explanatory variables collectively explain approximately 99.6 percent of the variation in the dependent variable. The Durbin–Watson
Table 1 2SLS estimates of structural parameters Demand equation Dependent variable=QDt
Short-run supply equation Dependent variable=PRt
Variables
Coefficients
Standard error
Variables
Coefficients
Standard error
Constant PRt ARRt ERt CPIt INCt RECt CRSt R2 Adj. R2 DW-Stat
7697.9960* 4.5084* 1.7095* 1.5862 71.7971* 0.0113 1022.9220** 3232.0800* 0.9964 0.9942 2.8240
2413.5110 1.9405 0.3589 15.6063 11.5271 0.2484 526.3907 874.3260
Constant QDt QCt PRt1 LABt OFFt1 CRSt
1844.6475** 10.0532* 16.4289* 1.1557* 0.3092* 0.0077* 1348.8908*
420.6567 0.0175 4.9082 0.2327 0.0773 0.0022 101.7226
R2 Adj. R2 DW-Stat
0.9483 0.9225 1.8589
Note: ‘‘*’’ and ‘‘**’’ indicate statistical significance at 5% and 10% levels, respectively.
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H. Qu et al. / Hospitality Management 21 (2002) 455–462
d-statistic of 2.8240 suggests lack of (first-order) serial correlation. Most of the explanatory variables are highly significant, except for ER and INC. The coefficient of PR suggests that a one-dollar hike in average room rate can cause a decrease of demand of about 4.5 rooms per day on average. Evaluated at the sample means, the demand elasticity is approximately 0.15, which is considerably lower (i.e. more inelastic) than Ismail and Hiemstra’s estimate (0.918) in 1994 and Fujii et al.’s (1985) estimate (0.953) in 1985. The coefficient of ARR indicates that for an increase of 1000 tourist arrivals in Hong Kong per year (or slightly below 3 arrivals per day), a daily demand of about 1.7 rooms is generated. This implies that at least 2 persons are sharing a room per day on average. The coefficient of REC suggests that the impact of western countries’ recessions during 1990–91 had a negative impact of about 1022 rooms per day, which is about a 5 percent drop in demand. The Asian financial crisis in 1997–98 caused a decline in demand of about 3232 rooms per day on average, or a drop of about 12 percent. It is not surprising that the variable INC is not significant. The demand for hotel rooms in Hong Kong is derived from international travel market. It is a little surprising that the effect of exchange rate movements is not significant as one might normally expect an appreciating Hong Kong dollar to effectively cause an increase in prices in Hong Kong, hotel room rate among them. One explanation for this lack of response to exchange rate movements is because travelers tend to look at the bilateral exchange rate between the US dollar and the Hong Kong dollar, which is essentially fixed as the Hong Kong dollar is pegged to the US dollar. But the ‘‘exchange rate’’ used in this study is a broader trade weighted exchange rate which the average traveler may not be aware of. It is also a little difficult to interpret the positive coefficient of the variable CPI. It would have been expected that CPI, similar to INC, largely pertains to the Hong Kong residents and hence it should not have a significant effect on hotel room price. However, a positive significant coefficient could be a sign that CPI is picking up the ‘‘time or trend effect’’ in the price of hotel rooms. The estimated short-run supply function also has a very good fit, with an adjusted R2 of 0.9483. Moreover, there is also lack of evidence of serial correlation as suggested by the Durbin–Watson d-statistic of 1.8589 (Strictly speaking, because the short-run supply equation is in an autoregressive form, Durbin’s htest should be applied. However, Durbin’s h-test is not very reliable in small samples.) All of the explanatory variables are found to be highly significant. Interestingly, there is indeed evidence that the short-run supply curve is slightly downward sloping, i.e. PR and QD are inversely related, as suggested by the negative coefficient of QD (0.0532), which implies a price flexibility of 1.6 at the sample means. This finding bears out the conjecture that, when faced with high excess room capacity in the short run, hotel operators could be lowering prices in an effort to raise room occupancy, giving rise to a slightly downwardsloping short-run supply curve. The hotel room occupancy rate also has a significant effect on room price in the short run. A one-percent increase in the room occupancy rate (less excess capacity) corresponds to a price hike of about 16 Hong Kong dollars.
H. Qu et al. / Hospitality Management 21 (2002) 455–462
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As expected, the current price is significantly impacted by the previous year’s price. The coefficient of PR lagged one year suggests that a HK$1.00 increase in previous year’s price is associated with about a HK$1.16 hike in current price. The cost of labor LAB, as a major item of short-run operating costs, is also found to have a significant impact on hotel room price. But the short-run effect is relatively small—daily room price rises only by an average of HK$0.31 for every one Hong Kong dollar increase in monthly labor cost. As mentioned above, the cost of Grade A private office could be exerting some effect on hotel room price. This is indeed the case as office price has a small positive coefficient, although the effect of office price is delayed by one year. There is no evidence that current office prices have a significant impact on current hotel room price. However, the short-run impact is relatively small. By one Hong Kong dollar increase in square foot price of Grade A office building, the average daily room rate is increased only by less than one cent (HK$0.0077). Finally, there is also evidence that the 1997–98 Asian financial crisis caused the Hong Kong hotel industry to lower room prices by as much as 25–30 percent. This was mainly because of the significant reduction of the number of tourist arrivals and the decrease in the demand for hotel rooms. As a short-run response, the lodging industry lowered room rates to attract more tourists in order to maintain a desirable occupancy rate.
4. Conclusions Overall, the demand and short-run supply equations are found to be highly significant based on the data. Through empirical implementation of the theoretical model, several important determinants of (short-run) supply and demand of the Hong Kong hotel industry are identified. On the demand side, hotel room price, tourist arrivals, the recession dummy and the Asian financial crisis dummy are highly significant. The goodness-of-fit of the demand model is very high, which suggests that these determinants of demand can reliably predict hotel room demand in Hong Kong. On the other hand, quantity demanded, hotel room occupancy rate, last period’s room price, labor cost, last period’s average price of Grade A private offices, and the Asian financial crisis all have significant influences on room price in the short run. The short-run supply model also fits the data very well and can, therefore, reliably predict hotel room price in Hong Kong.
References Fujii, Khaled, Mak, J., 1985. The exportability of hotel occupancy and other export taxes. National Tax Journal 38, 169–177. Hiemstra, S.J., Ismail, J.A., 1994. Analysis of impacts on supply and demand in the US lodging market. Paper Presented at the Annual Council on Hotel, Restaurant, and Institutional Education Conference, Palm Springs, CA, July 1994.
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Hong Kong Monthly Digest of Statistics, 1980–1998. Hong Kong Census and Statistics Department, Hong Kong Government. Hong Kong Property Review, 1980–1998. Rating and Valuation Department, Hong Kong Government. Hong Kong Quarterly Report of Wages, Salaries and Employee Benefits Statistics, 1980–1998. Hong Kong Government. Kennedy, P., 1992. A Guide to Econometrics, Third Edition. The MIT Press, Cambridge, MA.
Research note
A simultaneous equations model of the hotel room supply and demand in Hong Kong Hailin Qua,*, Peng Xub, Amy Tanc a
School of Hotel and Restaurant Administration, Oklahoma State University, 210 HESW, Stillwater, OK 74078, USA b Department of Economics, San Francisco State University, USA c School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong, SAR, China
Abstract The purpose of the study is to identify the important factors that influence the hotel room supply and demand, and their overall impact on the Hong Kong hotel industry. Nineteen years of time series data are used and a simultaneous equations econometric model is employed. The overall goodness-of-fit of both demand and supply models is very high, suggesting high predictive power. Empirical results indicate that ‘‘hotel room price’’ and ‘‘tourist arrivals’’ are significant factors driving the demand for hotel rooms. In addition, ‘‘1990–91 recession’’ and ‘‘the 1997–98 Asian financial crisis’’ had a significant negative impact on the demand for hotel rooms in Hong Kong. At the same time, ‘‘hotel room quantity demanded’’, ‘‘room occupancy rate’’, ‘‘last period’s room price’’, ‘‘labor cost’’, ‘‘last period’s average price of Grade A private offices’’, and ‘‘the Asian financial crisis’’ all have a significant impact on room price in the short run. r 2002 Elsevier Science Ltd. All rights reserved. Keywords: Supply and demand; Hong Kong hotel industry; Simultaneous equations
1. Introduction The imbalance between hotel room supply and demand in Hong Kong over the past 20 years or so has been a major concern of the Hong Kong hotel industry. Although lodging supply and demand in Hong Kong have grown at an annual average rate of 5.4 percent and 5.5 percent, respectively since 1980, such growths *Corresponding author. Tel.: +1-405-744-6711; fax: +1-405-744-6299. E-mail address: [email protected] (H. Qu). 0278-4319/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 8 - 4 3 1 9 ( 0 2 ) 0 0 0 3 1 - 2
456
H. Qu et al. / Hospitality Management 21 (2002) 455–462
have by no means been steady. Between 1985 and 1989, for instance, average daily hotel room supply grew at a rapid annual average rate of 8.6 percent, while average daily room demand increased at an annual average rate of 6 percent only. However, the demand growth surged ahead of the supply growth between 1990 and 1998. During this period, daily room demand increased by 5.4 percent, whereas daily room supply grew only 3.5 percent. A wide range of factors, both internal and external to the industry, have led to the unbalanced growth between the supply and demand for lodging in Hong Kong. The recession episodes in the major outbound countries in the early 1970s, 80s, and 90s, for instance, have been cited as the main explanation for the decline in hotel room demand in Hong Kong during those periods. In addition, the political uncertainty in the early 80s and 90s precipitated by the pending reversion of Hong Kong to the mainland China, coupled with the Tiananmen Square incident in 1989, were also noted as the main causes of the fluctuating room demand in Hong Kong. More recently, the Asian financial crisis during the late 90s must also have had a negative impact on the Hong Kong hotel market. On the other hand, the conversion of some hotels into Grade A office buildings with appreciating real estate values was reported as the most prevalent influence of hotel room supply decrease in the last 4 years. In 1993 and 1994, for example, seven hotels with 3000 rooms in Hong Kong were demoted and redeveloped into office buildings. At the same time, only a couple of new hotels with a total of 400 rooms were introduced into the market (The Bank of East Asia Economic Research Department, 1995). Although this trend of hotels being redeveloped into more profitable office buildings has slowed, it has by no means ended. The purpose of this study is to identify the important factors that influence the hotel room supply and demand in Hong Kong, and their overall impact on Hong Kong hotel industry, by using a simultaneous equations econometric model. This study is undeniably useful to help government, hotel developers, and investors understand the determinants of supply and demand in the hotel industry, and to reliably forecast future supply of and demand for hotel rooms in Hong Kong.
2. Model description The data set used in this paper consists of time series data of 19 annual observations from 1980 to 1998, which were obtained from various governmental sources and trade publications in Hong Kong. Hiemstra’s and Ismail (1994) supply and demand model for the US lodging market serves as the theoretical basis for the study. Accordingly, the structural model of the Hong Kong hotel industry consists of the following four equations: Demand Qd ¼ f ðPr ; Z1 Þ;
ð1Þ
Short-run supply Pd ¼ f ðQd ; Qc ; Z2 Þ;
ð2Þ
Long-run supply Qs ¼ f ðPr ; Z3 Þ;
ð3Þ
Equilibrium condition Qc ¼ Qd =Os ;
ð4Þ
H. Qu et al. / Hospitality Management 21 (2002) 455–462
457
where Qd is the demand for hotel rooms, Pr is the room rate or price, Qs the long-run room supply or room capacity and Qc the room occupancy rate, defined as the ratio of Qd to Qs : Econometric implementation of the full theoretical model would involve estimating the structural Eqs. (1)–(3). Unfortunately, data limitations have prevented us from estimating Eq. (3) with reasonable degree of reliability in this study. Therefore, Eq. (3) cannot be estimated without sufficient data. The simultaneous equation system of Hong Kong hotel market demand and short-run supply is specified as follows: Demand QDt ¼ f ðPRt ; ARRt ; ERt ; INCt ; CPIt ; RECt ; CRSt Þ þ ut ;
ð5Þ
Short-run supply PRt ¼ f ðQDt ; QCt ; PRt1 ; LABt ; OFFt1 ; CRSt Þ þ vt ;
ð6Þ
where t is the time subscript, ut the stochastic error term of demand function, vt the stochastic error term of short-run supply function, QD the average number of rooms occupied per day (Hong Kong Monthly Digest of Statistics, 1980–1998), PR the average daily room rate in Hong Kong dollars (Hong Kong Tourist Association), ARR the annual number of tourist arrivals in Hong Kong (in thousands), ER the exchange rate, defined as trade-weighted value of the Hong Kong dollar versus the currencies of the G-10 countries: Australian Dollar, Canadian Dollar, Dutch Guilder, French Franc, German Mark, Italian Lira, Japanese Yen, Swiss Franc, UK Sterling, US Dollar (Hong Kong Monthly Digest of Statistics, 1980–1998), INC the median household income in Hong Kong dollars (Hong Kong Census and Statistics Department), CPI the Hong Kong’s Consumer Price Index (Hong Kong Census and Statistics Department), REC the dummy variable representing the effect of the 1990–1991 recession in some major outbound countries, QC the room occupancy rate (in percent), LAB the Cost of labor in thousands of Hong Kong dollars, defined as average monthly salaries including fringe benefits for all hotel employees (Hong Kong Quarterly Report of Wages, Salaries and Employee Benefits Statistics, 1980–1988), OFF the average square foot price of Grade A private offices in Hong Kong dollars (Hong Kong Property Review, 1980–1998) and CRS the dummy variable representing the effect of the Asian financial crisis in 1997 and 1998. Quantity demanded QD and room price PR are taken to be simultaneously determined within the system of Eqs. (5) and (6). Eq. (5) is a demand function, as such, QD and PR are expected to be inversely related, i.e. the coefficient of PR is expected to be negative. On the other hand, the relationship between PR and QD in the short-run supply Eq. (6) cannot be predicted priori and need to be empirically determined. As suggested by Fig. 1, on an annual basis, there has always been excess capacity (i.e. Qs > Qd ) in the hotel market during the sample period. Therefore, in principle, the hotel industry can fill their rooms up to capacity without having to use price as a rationing device, implying that PR and QD are not necessarily positively related. In fact, PR and QD may even be inversely related because, when faced with high excess room capacity in the short run, hotel operators may try to lower prices in order to sell more rooms (especially to tourists) by offering discounts and package
H. Qu et al. / Hospitality Management 21 (2002) 455–462
458 35,000 32,500 30,000 27,500 # of Rooms
Average Daily Room Supply
25,000 22,500 Average Daily Room Demand
20,000 17,500 15,000 12,500 10,000 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Year
Fig. 1. Hong Kong hotel room supply and demand, 1985–1998.
deals, etc., as incentives. Consequently, it is possible for the short-run supply curve to be slightly downward sloping. Some important factors believed to have impacted Hong Kong’s hotel industry are treated as the exogenous variables in demand equation (5). The variable ARR, or the annual number of tourist arrivals in Hong Kong, is included in the demand equation as a major demand shifter. Since more arrivals translate into higher demand for lodging, ARR is expected to have a positive effect on QD. The exchange rate variable ER is included in the demand model to capture the effect of the relative costs of traveling to and from Hong Kong. The effect of ER is expected to be negative—an appreciation of the Hong Kong dollar, or an increase in ER, makes it relatively more expensive for international travelers to visit Hong Kong. Following standard demand modeling practice, the median Hong Kong household income INC and prices of other goods and services, measured by CPI, are also included in the demand model. These variables could have an impact on the local demand generated by local residents. However, since the primary source of demand for lodging is not from local residents, these factors are not expected to have a very strong influence, if any, on demand. The dummy variable REC is included to capture the negative effect of the 1990–1991 recession in the major outbound countries including the United States. Finally, the dummy variable CRS is also included to capture the negative impact of the Asian financial crisis (in 1997 and 1998) on the Hong Kong hotel market. Some important exogenous factors are included in the short-run supply equation (6). Since room prices are not completely independent from period to period, it is suspected that PR lagged one period or room price prevailing in the previous period might have a positive influence on the current price PR. Hotel room occupancy rate
H. Qu et al. / Hospitality Management 21 (2002) 455–462
459
is expected to have a positive effect on room price. The labor cost variable LAB is expected to have a positive effect on price, as hoteliers are likely to pass higher labor costs on to hotel customers. In the long run, higher prices of Grade A private office space can lead to increased conversion of hotel rooms into office buildings and (hence) a reduction in hotel room supply. In the short run, while total hotel room supply is fixed, higher office prices can at least have some effect on hotel room prices. Therefore, OFF lagged one period or the previous period’s average price of Grade A offices in Hong Kong, is included as an exogenous variable. Finally, the dummy variable CRS is intended to capture the negative impact of the Asian financial crisis on hotel room price.
3. Results and discussion A linear specification of the supply and demand model, consisting of Eqs. (5) and (6), is estimated by using the two-stage least-squares estimator (2SLS). All of the exogenous variables of the system are used as instruments for the endogenous variables. Since the number of annual observations is relatively small, 2SLS is particularly attractive, as it is likely to have small-sample properties superior on most criteria to all other estimators. It is also fairly robust in that it is insensitive to other estimating problems such as multicollinearity and specification errors (Kennedy, 1992). The parameter estimates of the model are summarized in Table 1. The estimated demand equation has an adjusted R2 of 0.9964, indicating a very good fit. In other words, the explanatory variables collectively explain approximately 99.6 percent of the variation in the dependent variable. The Durbin–Watson
Table 1 2SLS estimates of structural parameters Demand equation Dependent variable=QDt
Short-run supply equation Dependent variable=PRt
Variables
Coefficients
Standard error
Variables
Coefficients
Standard error
Constant PRt ARRt ERt CPIt INCt RECt CRSt R2 Adj. R2 DW-Stat
7697.9960* 4.5084* 1.7095* 1.5862 71.7971* 0.0113 1022.9220** 3232.0800* 0.9964 0.9942 2.8240
2413.5110 1.9405 0.3589 15.6063 11.5271 0.2484 526.3907 874.3260
Constant QDt QCt PRt1 LABt OFFt1 CRSt
1844.6475** 10.0532* 16.4289* 1.1557* 0.3092* 0.0077* 1348.8908*
420.6567 0.0175 4.9082 0.2327 0.0773 0.0022 101.7226
R2 Adj. R2 DW-Stat
0.9483 0.9225 1.8589
Note: ‘‘*’’ and ‘‘**’’ indicate statistical significance at 5% and 10% levels, respectively.
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d-statistic of 2.8240 suggests lack of (first-order) serial correlation. Most of the explanatory variables are highly significant, except for ER and INC. The coefficient of PR suggests that a one-dollar hike in average room rate can cause a decrease of demand of about 4.5 rooms per day on average. Evaluated at the sample means, the demand elasticity is approximately 0.15, which is considerably lower (i.e. more inelastic) than Ismail and Hiemstra’s estimate (0.918) in 1994 and Fujii et al.’s (1985) estimate (0.953) in 1985. The coefficient of ARR indicates that for an increase of 1000 tourist arrivals in Hong Kong per year (or slightly below 3 arrivals per day), a daily demand of about 1.7 rooms is generated. This implies that at least 2 persons are sharing a room per day on average. The coefficient of REC suggests that the impact of western countries’ recessions during 1990–91 had a negative impact of about 1022 rooms per day, which is about a 5 percent drop in demand. The Asian financial crisis in 1997–98 caused a decline in demand of about 3232 rooms per day on average, or a drop of about 12 percent. It is not surprising that the variable INC is not significant. The demand for hotel rooms in Hong Kong is derived from international travel market. It is a little surprising that the effect of exchange rate movements is not significant as one might normally expect an appreciating Hong Kong dollar to effectively cause an increase in prices in Hong Kong, hotel room rate among them. One explanation for this lack of response to exchange rate movements is because travelers tend to look at the bilateral exchange rate between the US dollar and the Hong Kong dollar, which is essentially fixed as the Hong Kong dollar is pegged to the US dollar. But the ‘‘exchange rate’’ used in this study is a broader trade weighted exchange rate which the average traveler may not be aware of. It is also a little difficult to interpret the positive coefficient of the variable CPI. It would have been expected that CPI, similar to INC, largely pertains to the Hong Kong residents and hence it should not have a significant effect on hotel room price. However, a positive significant coefficient could be a sign that CPI is picking up the ‘‘time or trend effect’’ in the price of hotel rooms. The estimated short-run supply function also has a very good fit, with an adjusted R2 of 0.9483. Moreover, there is also lack of evidence of serial correlation as suggested by the Durbin–Watson d-statistic of 1.8589 (Strictly speaking, because the short-run supply equation is in an autoregressive form, Durbin’s htest should be applied. However, Durbin’s h-test is not very reliable in small samples.) All of the explanatory variables are found to be highly significant. Interestingly, there is indeed evidence that the short-run supply curve is slightly downward sloping, i.e. PR and QD are inversely related, as suggested by the negative coefficient of QD (0.0532), which implies a price flexibility of 1.6 at the sample means. This finding bears out the conjecture that, when faced with high excess room capacity in the short run, hotel operators could be lowering prices in an effort to raise room occupancy, giving rise to a slightly downwardsloping short-run supply curve. The hotel room occupancy rate also has a significant effect on room price in the short run. A one-percent increase in the room occupancy rate (less excess capacity) corresponds to a price hike of about 16 Hong Kong dollars.
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As expected, the current price is significantly impacted by the previous year’s price. The coefficient of PR lagged one year suggests that a HK$1.00 increase in previous year’s price is associated with about a HK$1.16 hike in current price. The cost of labor LAB, as a major item of short-run operating costs, is also found to have a significant impact on hotel room price. But the short-run effect is relatively small—daily room price rises only by an average of HK$0.31 for every one Hong Kong dollar increase in monthly labor cost. As mentioned above, the cost of Grade A private office could be exerting some effect on hotel room price. This is indeed the case as office price has a small positive coefficient, although the effect of office price is delayed by one year. There is no evidence that current office prices have a significant impact on current hotel room price. However, the short-run impact is relatively small. By one Hong Kong dollar increase in square foot price of Grade A office building, the average daily room rate is increased only by less than one cent (HK$0.0077). Finally, there is also evidence that the 1997–98 Asian financial crisis caused the Hong Kong hotel industry to lower room prices by as much as 25–30 percent. This was mainly because of the significant reduction of the number of tourist arrivals and the decrease in the demand for hotel rooms. As a short-run response, the lodging industry lowered room rates to attract more tourists in order to maintain a desirable occupancy rate.
4. Conclusions Overall, the demand and short-run supply equations are found to be highly significant based on the data. Through empirical implementation of the theoretical model, several important determinants of (short-run) supply and demand of the Hong Kong hotel industry are identified. On the demand side, hotel room price, tourist arrivals, the recession dummy and the Asian financial crisis dummy are highly significant. The goodness-of-fit of the demand model is very high, which suggests that these determinants of demand can reliably predict hotel room demand in Hong Kong. On the other hand, quantity demanded, hotel room occupancy rate, last period’s room price, labor cost, last period’s average price of Grade A private offices, and the Asian financial crisis all have significant influences on room price in the short run. The short-run supply model also fits the data very well and can, therefore, reliably predict hotel room price in Hong Kong.
References Fujii, Khaled, Mak, J., 1985. The exportability of hotel occupancy and other export taxes. National Tax Journal 38, 169–177. Hiemstra, S.J., Ismail, J.A., 1994. Analysis of impacts on supply and demand in the US lodging market. Paper Presented at the Annual Council on Hotel, Restaurant, and Institutional Education Conference, Palm Springs, CA, July 1994.
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