The long-run tourism effect of historical celebrities: Evidence from one of the most influential literatus in China

Abstract

Do historical celebrities contribute to city tourism today? While the existing literature has widely examined the tourism effect of modern film celebrities, it has not yet explored the long-run impact of historical and cultural celebrities on tourism economies. We answer this question by tracing the places of residence of Su Shi, one of the greatest Chinese cultural celebrities in the Northern Song Dynasty (960–1127), and estimating the effect on average city tourism between 2002 and 2019. Our ordinary least square estimation finds that one more month of Su Shi’s residence increases domestic tourism revenue today by about 0.3%, leading to an average tourism value of around 118 million Chinese Yuan (about 18 million US dollars). We consolidate the long-run effect with several robustness checks. Channel analysis further shows that his residence facilitates tourism development today and increased cultural heritage in subsequent dynasties. These findings highlight the roles of historical celebrities in fostering cultural heritages and forming city tourism competitiveness.

Keywords

city tourism historical celebrity long-run effect cultural heritage China

JEL Code:

Z32; L83; Z11

Introduction

While the tourism industry has become an indispensable component of the modern national economy, the competition in domestic and global tourism markets has become highly intense. To consolidate tourism competitiveness, local tourism stakeholders can take full advantage of unique local tourism resources, especially cultural heritage. Culture is a positive aspect for individuals and society as a superior source of satisfaction (Scitovsky, 1989), and thus has real value (Melstrom, 2014; Navrud and Ready, 2002). This has been manifested in mounting visitors to cultural World Heritage Sites (WHSs) such as the Forbidden City in China, the pyramids in Egypt, the Eiffel Tower in France, and the Statue of Liberty in the USA. At the same time, local tourism stakeholders have realized and used resources and properties related to celebrities to develop tourism economies (Glover, 2009). Tourism development based on celebrities and cultures has been a salient feature in China which has an unbroken history of over 5000 years of well-recorded human activities, leading to numerous celebrities, abundant relics, and colorful cultures (Sarah Li, 2008).

Despite the importance of historical celebrities in local tourism development, the literature remains rare in examining the effect of celebrities in history on city tourism now. Prior works have broadly examined the tourism impacts of WHS inscription, modern celebrities, and cultural goods and services. For example, empirical studies have tested the tourism effects of WHS inscription though the findings are highly inconclusive (Adie et al., 2018; Cuccia et al., 2017; De Simone et al., 2019; Gao and Su, 2019; Huang et al., 2012; Yang et al., 2010, 2019). Meanwhile, evidence has also emerged to show the roles of modern celebrities in promoting destination tourism (Glover, 2009; Kim et al., 2019; Lee et al., 2008; Xu and Pratt, 2018), as well as the values of cultural products and services in attracting tourists and enhancing city attractiveness (Van Loon et al., 2014). However, there is a gap in investigating the tourism value of historical celebrities whose relics in a city consist of important cultural heritage elements. Visiting relics to memorize the footprints of historical celebrities and events is a salient feature of cultural tourism. This enables tourists to form a unique experience to dialogue with historical celebrities and perceive historical events more intensively and authentically. Students can deepen their knowledge of the works of historical celebrities they learned from textbooks in class. Therefore, places with relics of historical celebrities and events can fulfill these nostalgic demands, thereby having an advantage in developing local tourism economies.

We try to bridge the research gap in evaluating the long-run tourism effect of historical celebrities. To this end, we use Su Shi, one of the most influential literatus in Chinese history, as a case study. Born in 1036 AD and dying in 1101, Su Shi first became a Jinshi (Imperial Scholars who had the highest degree in the imperial examination and were candidates of government officials in Imperial China) in 1056 when he passed the imperial examination with his paper ranked second. He was soon acknowledged as the most influential and famous celebrity both in his time and after his death. Because of his outstanding contribution to Classical Chinese works, local and national governance, and gourmet food, he gained many titles—poet, calligrapher, painter, scholar, politician, philanthropist, engineer, and gourmand. He was so popular and adored by the Chinese that his works were well preserved, and his life had been carefully recorded. His verses have been printed in textbooks and recited by Chinese students. Relics associated with him are well protected and preserved to commemorate his virtue and benevolent rule as a local governor. While it is documented that public ignorance of traditional culture negatively affects perceptions of authenticity, as shown by Zhou et al. (2013) in the case of the Chinese calligraphic landscape, Su Shi’s popularity over the centuries removes such ignorance. Therefore, Su Shi could substantially influence tourism economies today in places he resided through his relics and later accumulation of cultural heritage.

By tracing Su Shi’s places of residence as a minor, an official, or when demoted, we calculate the exact lengths of his residence in 16 places and match them with the average domestic tourism revenue of Chinese cities between 2002 and 2019. Spatial variations in these lengths are thus explored as a plausibly exogenous shock on the abundance of local historical celebrities to identify the causal effect on city tourism economies. This is first because both his residence locations and lengthens were historical events exogenous to determinants of tourism economies, thereby no concern of a reversed causality. Moreover, Su Shi could not determine his dwelling place. While nobody can select her birthplace, officials in the North Song Dynasty could hardly choose where to work. Instead, their work locations were determined by job vacancies and the imperial court, particularly the emperors who had supreme power in Imperial China. Therefore, Su Shi’s residence locations were due to political reasons and thus arguably exogenous to other long-run determinants of modern tourism economies.

The ordinary least squares (OLS) estimation shows that Su Shi produces a persistent tourism effect in the cities where he resided. Su Shi’s one additional month stay in a city will increase domestic tourism revenue today by 0.25%–0.41%, depending on controls included. The effect is non-trivial, suggesting an increase in average tourism revenue of 98.24–161.12 million Chinese Yuan (RMBs), which account for 0.61%–0.99% of average city domestic tourism revenue between 2002 and 2019.

We conduct several robustness checks to confirm the long-run effect, first using alternative measures of Su Shi’s stay in a city and the tourism outcome. We then change observations by including provincial capitals, confining the cities within the territory of the Northern Song Dynasty, removing the capital at the time, or removing cities only having Su Shi’s traveling stops. Moreover, we control more covariates nowadays and in history to raise the estimation precision and alleviate the omitted variable bias. Besides, to make cities with and without Su Shi’s residence more alike, we construct a matched data set with the historical administration information and the distance to the then capital. Finally, given Su Shi and his works are hard to understand by foreigners, we perform an informal falsification test which shows that Su Shi’s residence has an insignificant effect on inbound tourism outcomes. All these robustness checks lead to consistent evidence that Su Shi contributes to current tourism economies in the cities where he dwelled.

Su Shi also motivated generations of Chinese students to study hard and become a talent like him, resulting in a subsequent accumulation of cultural heritage in the cities where he resided. He also attracted later literatus and his fans to visit sites with his relics, which enriched local cultural heritage. Both effects facilitate city tourism development today. We thus test these key channels by first estimating the effect of his residence on local tourism development and then the effect on city cultural heritage. These channel analyses show that his residence increased the number of high-level tourist attractions today, the subsequent Classical Chinese works in the Song dynasties, and the number of Jinshi in the Qing Dynasty in cities where he resided. We thus reassure Su Shi’s long-run tourism impact.

By estimating the long-run tourism effect of Su Shi, we contribute to the existing literature in three ways. First, we enrich the literature on celebrity-induced tourism by estimating the long-run tourism effect of a historical rather than modern celebrity. This strand of literature has extensively explored the roles of movie stars in shaping tourism demand, including the endorsement role of celebrities in tourism promotion (Glover, 2009; Xu and Pratt, 2018) and the effects of celebrity involvement on destination image, place attachment, and tourists’ visiting and purchasing behaviors (Chen, 2018; Kim et al., 2019; Lee et al., 2008; Wong and Lai, 2015). These prior studies mostly use tourist-level survey data and methods such as confirmatory factor analysis and structural equation models. In contrast, we construct city-level data by matching the residence information of Su Shi with current city statistics and try to identify the causal effect of the historical celebrity.

Second, since Su Shi is one of the most influential cultural celebrities in Chinese history, we add to the literature on the valuation of cultural goods and services (Noonan, 2003; Throsby and Zednik, 2014; Wiśniewska et al., 2020), which rarely evaluates the effect of a cultural celebrity. Specifically, it has been argued that culture can raise subjective well-being and improve social welfare (Scitovsky, 1989; Tubadji et al., 2015; Wheatley and Bickerton, 2017), attract tourists and enhance city attractiveness (Van Loon et al., 2014), foster innovation (Dalle Nogare and Murzyn-Kupisz, 2021), and promote growth (Backman and Nilsson, 2018). However, it is unknown if and how cultural celebrities in history can display tourism influences today. We bridge this research gap in the literature on cultural tourism by using Su Shi, perhaps the most influential literatus in Chinese history, as a case to disentangle the long-run tourism impact of cultural celebrities.

Third, we also add to the place-based tourism development literature which documents local cultures and heritages are important resources for tourism economies (Backman and Nilsson, 2018; Sarah Li, 2008; Smith, 2015; Van Loon et al., 2014). In contrast to other historical celebrities, Su Shi’s life was well recorded, allowing us to distinguish his lengths of residence across Chinese cities. We can thus use them to identify the causal effect on city tourism nowadays. In addition to an aggregate effect, we test some key channels to confirm the causal effect. We reveal that Su Shi’s residence cities have more high-level tourist attractions, Classical Chinese works, and cultural literatus in subsequent dynasties. Therefore, we extend the place-based tourism development literature by showing that historical celebrities can be a vital source for local cultures and heritages and thus tourism economies.

The rest of the paper is structured as follows. We first briefly introduce Su Shi and his traces in China and discuss his influences on city tourism today based on the existing literature in the next section. We then specify the empirical strategy, report the main results, conduct robustness checks, and test two channels at work in subsequent sections. The paper concludes in the last section.

Background

Su Shi and his footprints

On December 19, 1036, Su Shi, also known as Su Tungpo, was born to an affluent family in Meizhou, now the city of Meishan in the province of Sichuan.¹ He was a gifted child and usually praised by teachers at the private school he attended. In May 1056, Su Shi, together with his father, Su Xun, and his younger brother, Su Zhe, arrived in Kaifeng, the capital, and passed the imperial examination in the autumn.² In the following year’s palace examination, his paper was ranked second among 388 examinees, and he was thus enrolled as a Jinshi. Because of his talents in composing verses and essays, Su Shi soon became known to the palace, the officialdom, and the literati. He also remains greatly popular today due to his achievements in Classical Chinese literature, his benevolent rule when serving as a local governor, and his virtue. The Chinese people liked him so much that his life and works, including poems, paintings, and calligraphies, have been well recorded and preserved.

However, Su Shi’s political life was full of bizarre twists and turns, resulting in his rich residence experience in a dozen places. Besides his homeland, Meizhou, and the capital, Kaifeng, he first stayed in the county of Fengxiang, now a district of the city of Baoji in the province of Shaanxi, as a low-level local official. He was called back to the capital and then stayed in his homeland due to his father’s death in 1066. After that, he was appointed as an official in the central government several times, reaching the position of minister at several central government departments. He also served as local governor in seven prefectures, including Hangzhou, Xuzhou, Yangzhou, etc. Meanwhile, due to failure in political competition, Su Shi was also exiled to three remote places—Huangzhou, Huizhou, and Danzhou. The great poet was afflicted by dysentery on the way home (Lin, 1948) after the palace called him back from Danzhou, and he died in Changzhou in July 1011. During his 64 years of life, Su Shi traveled to 183 locations (Wang, 2017) and left 2,727 poems (Li et al., 2021).

Detailed information on Su Shi’s places of residence allows us to examine his tourism value for a city today. We trace his footprints according to the data from Wang (2017) and collect a list of all the places he visited. We also refer to the biography by Lin (1948) and identify 16 places from 11 provinces where Su Shi resided (see also online appendix Table A1 for detailed information). The locations of these places are marked in Figure 1, with red dots denoting cities he resided in and black ones the places he traveled to. It shows that his footprints stretch over the map of modern China, with the capital Kaifeng as the center, from the west (where his homeland was located) to the east (Hangzhou), and from the north (Dingzhou) to the southernmost (Danzhou).

Figure 1.

Cities where Su Shi resided and visited. Note: the places with Su Shi’s residence are denoted with the current city name.

We focus on 16 places where Su Shi resided rather than those he only traveled to because his residence in these cities is more exogenous to his own decisions and the tourism of these cities. In ancient China, intellectuals, taught by Confucian ethics, had a strong mission to serve the emperor. Although they could refuse a palace appointment, or as Su Shi did, ask for an appointment as a local official, it was unlikely that they were able to choose a position in the government. Therefore, Su Shi’s places of residence were not determined by himself. When favored by the emperor, Su Shi worked in the capital or developed cities like Hangzhou; when out of favor with the emperor and the official party in power, he was framed and jailed in the capital or exiled to remote places like Huangzhou, Huizhou, and Danzhou.

Among the 16 cities, cities like Kaifeng and Hangzhou, which were political or economic centers at the time, have more tourism resources, but the rest of these cities may not have had such an advantage in tourism resources before Su Shi’s arrival. However, places where he traveled but did not reside might be less exogenous to determinants of cultural tourism because Su Shi could choose to visit places with rich heritages. For example, in early 1084, when the palace ended his first exile in Huangzhou, he traveled to Lushan Mountain, a famous tourist attraction even before his time and now a WHS. Because of this selection, including places where Su Shi traveled to identify the causal effect may overestimate the tourism effect of Su Shi. Meanwhile, many visits were too short for the poet to leave any tangible heritage specific to him but some poems. Given the plausible exogeneity of Su Shi’s residences in the 16 cities, we mainly rely on variations in the length of his residence to identify the current tourism effect of the great poet.

Related literature

Although the long-run effect of historical celebrities on tourism economies is rarely examined, our work is closely related to the three strands of literature: celebrity-induced tourism, place-based tourism development, and heritage tourism. First, film celebrities (or stars) as an indispensable part of movies play a critical role in understanding film-induced tourism economies. The literature has documented that celebrities can endorse the destination image and help advertise the destination and celebrity-related products (Glover, 2009; Xu and Pratt, 2018). Tourists thus perceive a better image of and attach more to the celebrity-endorsed places and have a higher willingness to recommend, visit, and pay for these places than those without a celebrity endorsement or involvement (Chen, 2018; Kim et al., 2019; Lee et al., 2008; Wong and Lai, 2015). In addition, Yen and Croy (2016) found with questionnaire data from Taiwan that celebrity worship plays a mediation effect between the nexus of celebrity involvement and destination image. Therefore, film celebrities can have positive tourism values through their endorsement for and participation in destination image as well as through fans’ worship. These rationales could also apply to analyzing a historical celebrity's tourism effects. However, historical celebrities differ from modern stars because they have more persistent cultural, educational, and economic implications. This is just what the title of historical celebrity means. Indeed, a historical celebrity has passed the test of time and thus could produce a more persistent and pronounced tourism effect than a modern one.

Second, the present paper is also related to the broader cultural tourism literature, particularly the place-based cultural tourism development proposed by Smith (2015). Su Shi is a cultural celebrity with outstanding achievements in Classical Chinese works learned and recited by generations of Chinese students and intellectuals. Culture has magical but unignorable effects on both individuals and society. As Scitovsky (1989) argued, “culture comprises some of the best, most valuable things life has to offer” (p. 1). It has functions of raising subjective well-being and improving social welfare (Scitovsky, 1989; Tubadji et al., 2015; Wheatley and Bickerton, 2017), having substantial value to the human society (Melstrom, 2014; Navrud and Ready, 2002; Noonan, 2003; Throsby and Zednik, 2014; Wiśniewska et al., 2020). Since cultures are locally created, different from one region to another, and usually have larger local effects, they are important place-based resources for regional attractiveness and growth and facilitate local tourism development (Backman and Nilsson, 2018; Sarah Li, 2008; Van Loon et al., 2014).

Unlike other celebrities, great celebrities in history like Su Shi ignited local cultural heritage that flourished due to later literati inspired or attracted to visit places where they stayed. This also links our work to the growing literature on heritage tourism, particularly about the tourism effect of the World Heritage Site (WHS) inscription. Because the WHS title is only designated to properties with outstanding universal values, gaining the inscription signals credible tourism quality and thus attracts tourists to visit destinations with inscribed properties. However, empirical evidence is highly mixed. While some support the tourism promotion effect of the inscription (De Simone et al., 2019; Yang et al., 2010; Zhang et al., 2022), others fail to find such an effect (Adie et al., 2018; Gao and Su, 2019) or find a limited impact in attracting international tourists (Huang et al., 2012) and raising tourism efficiency (Cuccia et al., 2017). This mixed evidence can be explained by the differences in the data and the method used, as concluded by Yang et al. (2019). Nevertheless, heritages can be a pertinent aspect of tourism development and contribute to local tourism economies. We differ from these studies in that we extend the study horizon of the heritage-tourism literature to the maker of heritages. Specifically, we use the great poet Su Shi as a case to examine the long-run tourism effect of cultural celebrities and explore later local heritage accumulation as a critical channel at work.

The tourism impact of Su Shi’s residence

The literature on celebrity-induced tourism and place-based cultural tourism development underpins the tourism promotion effect of historical celebrities. Given his big name and his fantastic works in Classical Chinese, Su Shi can serve as a somewhat extreme but ideal case to identify the effect of historical celebrities on tourism development today.

As, perhaps, China’s most influential historical literati, Su Shi should have much more pronounced implications for tourism development nowadays than both modern celebrities and other historical celebrities. His stories have been told generations by generations, and Chinese students frequently recite his works from textbooks. More importantly, his footprints have been well recorded, protected, and preserved, and his relics have been developed as tourist attractions or memorial halls. Tourists are thus attracted to visit these relics which allow them to have a mental dialogue with the great poet across time by standing at the same place where he resided.³

Moreover, Su Shi added to the cultural heritage of places he resided through the traces he left and his persistent influence on local cultural heritage. As an idol of Chinese literati, he motivates local people to study hard and become a talent like him. For example, it was recorded that the first Jinshi in Hainan province, the least developed area at the time, was Su Shi’s student he taught during his exile time in Danzhou. Because of his residence, later literati followed his traces and composed verses in places he stayed. As a result, cultural heritage was accumulated over the generations in places he lived, which we will test in the channel analysis.

To elaborate on how Su Shi can promote the tourism economy today in the cities where he dwelled, we only need to conduct a simple equilibrium analysis of the city tourism market, as graphed in Figure 2. The tourism revenue of a city is determined jointly by the supply and demand sides of tourism products and services, which attain a market-clearing price and tourist arrivals at the point of intersection E0. The revenue can thus be shown as the area of P0OQ0E0. A historical celebrity’s residence adds to the city tourism market in two ways. Owing to its uniqueness and as cultural heritage, having the residence first increases tourism supply by shifting the supply curve S0 right to Ss. Meanwhile, the tourism demand is boosted since his relics can attract tourist arrivals by providing a unique touring experience to understand and connect with the celebrity. As a result, the demand curve D0 would also be shifted rightward to Ds. The consequent equilibrium move to Es, and the tourism revenue is the area of PsOQsEs. While the caused change in the market price is unclear, the tourist volume will increase. The resulting tourism revenue will also increase because the supply of cultural tourism is usually inelastic while the demand for it is elastic. This can be manifested by comparing the area PsOQsEs with P0OQ0E0. Therefore, we propose the following case-specific research hypothesis:

Figure 2.

The roles of a historical celebrity in the city tourism market.

Su Shi can produce a persistent and positive effect on the tourism economy nowadays in the cities where he resided.

Empirical strategy

We use the following empirical model to estimate the long-run tourism effect of Su Shi

L n ({\bar{T o u r i s m_R e v e n u e}}_{i, 2002 - 2019}) = c + α S u s h i_S t a y_{i, s o n g} + {\bar{X}}_{i, 2002 - 2019} β + ε_{i}

(1)

where the outcome variable,

{\bar{T o u r i s m_R e v e n u e}}_{i, 2002 - 2019}

, is the average tourism revenue of city i between 2002 and 2019,

S u s h i_S t a y_{i, s o n g}

is the months that Su Shi resided in city i in the Northern Song Dynasty, and

{\bar{X}}_{i, 2002 - 2019}

is a vector of control variables regarding regional dummies and city characteristics which are also averages between 2002 and 2019, and

ε_{i}

is the error term. Our identifying assumption is that given the control variables, Su Shi’s stay is not determined by omitted variables in the error term affecting tourism outcomes, that is,

E (S u s h i_s t a y_{i, s o n g}, ε_{i} | {\bar{X}}_{i, 2002 - 2019}) = 0

. While it is unlikely that these controls can determine the months of Su Shi’s residence in a city, we control them to increase the estimation precision because they are determinants of city tourism, as suggested by Cinelli et al. (2020). For the same purpose, we also take the natural logarithm to the outcome variable and some city-level covariates. The estimate

α

measures the size of a one-month residence on city average tourism revenue between 2002 and 2019. To attain conservative significance levels, we report robust standard errors that control for heteroscedasticity.

The data used to calculate averages of the tourism outcome and its determinants are taken from China City Statistical Yearbooks compiled by the National Bureau of Statistics (2003–2020). Although official statistics on these variables are available for 2000 and 2001, there are too many missing values in tourism outcomes in both years.⁴ The investigation period stops in 2019, the last year before the tourism economy was interrupted by the COVID-19 pandemic. The outcome variable, tourism revenue, is measured with the domestic tourism receipts which consist of all expenditures of domestic tourists on transportation, sightseeing, accommodation, dining, shopping, and entertainment during their traveling and touring. We use domestic tourism receipts rather than total tourism receipts from both domestic and inbound tourists because Su Shi is much more well known to Chinese people than to foreigners, as a great poet, a painter, a calligrapher, and a competent and benevolent official. As a result, inbound tourists may not be attracted by historical sites related to Su Shi because Su Shi’s works were written in Classical Chinese, making them difficult for foreigners to perceive and appreciate their meaning and beauty. To show this, we will estimate the effect of Su Shi’s stay on inbound tourism outcomes as falsification tests, providing contrast results to its impact on domestic tourism revenue. We also use domestic tourist arrivals as the outcome variable to consolidate our main results.

The variable of our interest is the length of residence of Su Shi (Su Shi’s stay) in each city. As introduced above, we mainly focus on the cities where Su Shi stayed as an official, a resident, or an exiled political criminal. According to the biography written by Lin (1948), we find that during his 64 years of life, Su Shi resided in 16 cities, with the longest stay in his homeland, Meishan, for about 24 years, a total of 286 months. His shortest stay occurred in Dengzhou, now the city of Yantai in Shandong Province, where he only stayed for about half a month. We rescaled these stays into the number of months, with a minimum of one month if he resided in a place for less than 30 days.⁵ Other cities are denoted as without his stay, and we assigned his stay length in these cities with 0. We do not count Su Shi’s travel stops in a city as his residence, firstly because these stops were too short for him to leave any tangible heritage for tourism development today. This is also because, as we have argued in Section 2.1, his traveling stops are more selective than his residence in a city. In a robustness check, we will include a variable of his traveling stops to see how this will change our main results.

Control variables first include two important city tourism determinants—GDP per capita and population density. The GDP per capita is the most comprehensive indicator of residents’ income, determining the domestic demand for cultural tourism. To measure local and outside demands for tourism, we used city i’s own GDP per capita and a distance-weighted GDP per capita of all cities but city i, respectively. Specifically, the outside demand for tourism in city i ( $G D P_P C_{i o t}$ ) is calculated as the sum of all other cities’ GDP per capita ( $G D P_P C_{j t}$ , $j \neq i$ ) divided by their respective coordinate distance to city i ( $D i s t a n c e_{j i}$ ), that is, $G D P_P C_{i o t} = \sum_{j, j \neq i} G D P_P C_{j t} / D i s t a n c e_{j i7}$ . We weight the outside tourism demand with the distance between cities simply because the demand for tourism in city i from city j would decrease with the distance between them. Population density is used to measure the extent of economic agglomerations which can facilitate the division of labor and specialization to provide comfortable tourism amenities. Local tourism resources also determine a city’s tourism revenue. Cities with unique tourism resources have a comparative advantage in developing tourism economies. We use three variables to capture tourism resources—the number of WHSs, five-As (the top grade) tourist attractions (5ATAs), and top tourist city (TTC) designation. These control variables have been documented as measures of tourism demand or quality (Albalate and Fageda, 2016; Chen and Haynes, 2015; Gao et al., 2020; Gao and Su, 2021; Massidda and Etzo, 2012). We use averages of these variables, which, except for three tourism resource variables, are calculated from the data from China City Statistical Yearbooks. Three tourism resource variables are taken from Gao and Su (2021) (see online Appendix Table A2 for a summary of variables and data sources). Finally, we control for some regional dummies to take away regional differences in tourism economies. These regional dummies include three regional dummy variables—east, central, and west regions—and a dummy variable denoting coastal provinces (see online Appendix Table A3 for details on these regions).

By merging the historical data on Su Shi’s residence with the averaged city-level data between 2001 and 2015, we attain cross-sectional data for 288 Chinese cities. We remove four megacities: Beijing, Shanghai, Tianjin, and Chongqing, and 27 provincial capitals because these cities are national or regional political, economic, and tourism centers, thereby differing remarkably from other cities. In other words, we mainly use the data from 257 prefectural-level cities. Nevertheless, we will show in a robustness check that including provincial capitals does not alter our main results.

Table 1 reports summary statistics. It shows that the mean of average domestic tourism revenue is 16.24 billion RMBs, with a maximum of 114 billion RMBs from Suzhou, one of the most popular tourist cities in China. The mean of average domestic tourist arrivals is about 17 million people, also with a maximum value from Suzhou. The mean of Su Shi’s residences is 2.42 months, with the longest stay of 286 months in Meizhou, his homeland. In the last three columns, we report the means of main variables by Su Shi’s residence status and their mean differences. They show that cities where Su Shi resided have much greater domestic tourism revenue, more tourist arrivals, denser populations, and more 5ATAs than those without his residence. However, there is no significant difference between the two groups according to the means of GDP per capita, the number of WHSs, and top tourist city designation.

Table 1.

Summary statistics of main variables.

Variable	Prefectural cities excluding provincial capitals (257 cities)				(1) With Su Shi’s residence (14 cities)	(2) Without Su Shi’s residence (243 cities)	(1) − (2)
Variable	Mean	Std. Dev.	Min	Max	Mean	Mean	Mean difference
Domestic tourism revenue (10,000 RMBs)	1,623,874	1,533,300	32,669.69	11,400,000	3,204,597	1,532,804	1,671,793***
Domestic tourist arrivals (1,000 people)	17,048.64	11,987.81	377.74	74,600.93	29,156.89	16,351.05	12,805.84***
Su Shi’s stay (months)	2.42	20.27	0	286	44.36	0	44.36***
GDP per capita (RMB)	34,949.80	29,388.47	7,264.44	370,414.90	43,514.93	34,456.33	9,058.60
Distance-weighted GDP per capita of other cities	14,716.42	16,408.73	2,481.05	175,726.30	21,591.94	14,320.30	7,271.64
Population density (population/km²)	400.18	301.58	5.26	2,487.62	612.03	387.97	224.06***
No. of WHSs	0.51	0.64	0	3.00	0.64	0.50	0.15
No. of 5ATAs	0.30	0.54	0	3.78	0.63	0.28	0.36***
Top tourist city	0.12	0.32	0	1.00	0.21	0.11	0.10

Notes: All variables except Su Shi’s stay are the average between 2002 and 2019. *** denotes the significance level of 1%.

Main results

Table 2 reports the main results by estimating model (1) with the OLS method. We do not control for any covariates in column (1), only include three regional dummies in column (2), then also control for GDP per capita, distance-weighted GDP per capita of other cities, and population density in column (3), and further control three tourism quality variables in column (4). Regression results show that the estimate of Su Shi’s stay is positive in all specifications and is statistically significant after controlling for some covariates. Without any controls, Su Shi’s stay increases the average domestic tourism revenue, though the effect is at the marginal significance level of 10% (see column (1)). However, once regional dummies are included to consider regional differences in tourism development, the effect becomes much larger and statistically significant (see column (2)). The estimate remains significant and positive as we further control for city-level covariates, ending with a magnitude of 0.0028 (see column (4)). These results reveal that Su Shi’s one-month additional residence is associated with an increase in domestic tourism revenue today by about 0.3%.

Table 2.

Main results.

Variable	(1)	(2)	(3)	(4)
Variable	Ln (domestic tourism revenue)
Su Shi’s stay	0.0025*	0.0041***	0.0027***	0.0028***
Su Shi’s stay	(0.0014)	(0.0012)	(0.0009)	(0.0006)
Central region	—	−0.0250	0.2176	0.2949
Central region		(0.2222)	(0.2131)	(0.1832)
Western region	—	−0.4180***	0.1213	0.1822
Western region	—	(0.1439)	(0.1644)	(0.1448)
Coastal provinces	—	0.7419***	0.6563***	0.6650***
Coastal provinces	—	(0.1817)	(0.1739)	(0.1512)
Ln (GDP per capita)	—	—	−0.0232	0.0257
Ln (GDP per capita)	—	—	(0.2494)	(0.2013)
Ln (distance-weighted GDP per capita of other cities)	—	—	0.4382**	0.2050
Ln (distance-weighted GDP per capita of other cities)	—	—	(0.1979)	(0.1597)
Ln (population density)	—	—	0.2525***	0.3071***
Ln (population density)	—	—	(0.0753)	(0.0725)
Number of WHSs	—	—	—	0.1452**
Number of WHSs	—	—	—	(0.0736)
Number of 5ATAs	—	—	—	0.5878***
Number of 5ATAs	—	—	—	(0.0920)
Top tourist city	—	—	—	0.2626**
Top tourist city	—	—	—	(0.1067)
Constant	13.8838***	13.7135***	8.2347***	9.2662***
Constant	(0.0638)	(0.1989)	(1.4617)	(1.2887)
Observations	257	257	257	257
R-squared	0.0025	0.2107	0.3338	0.4706

Notes: Robust standard errors are in parentheses; *, **, and *** denote the significance level of 10%, 5%, and 1%, respectively.

One may wonder if the effect of Su Shi’s stay is too small since the estimate is about 0.003. To see this, we use the estimates in Table 2 and the means of Su Shi’s stay and the average domestic tourism revenue between 2002 and 2019 to calculate the tourism value. Given the means of both variables reported in Table 1, the tourism value can be calculated as 98.24–161.12 million RMBs ( $\hat{α}$ × 2.42 × 16,238,740,000). These values are non-trivial since they account for 0.61%–0.99% of city average tourism revenue in the 18 years.

Robustness

Using alternative measures

The first set of robustness checks uses alternative measures of the city tourism outcome and Su Shi’s stay in a city. One may argue that Su Shi’s residence can be better captured by his stay or not than stay months. In other words, the extensive margin of Su Shi’s stay might be more substantial for city tourism than the intensive margin. To examine this, we regress domestic tourism revenue with a dummy variable regarding Su Shi’s stay. Column (1) of Table 3 reports the regression result, which shows that at the 5% significance level, cities with Su Shi’s stay have a 26.7% higher domestic tourism revenue than those without his stay.

Table 3.

Robustness checks with alternative measures.

Variable	(1)	(2)	(3)	(4)
Variable	Ln (domestic tourism revenue)		Ln (domestic tourist arrivals)	Ln (domestic tourism revenue in 1999 price level)
Su Shi’s stay (a dummy measure)	0.2668**	—	—	—
Su Shi’s stay (a dummy measure)	(0.1271)	—	—	—
Su Shi’s stay (counting Yantai and Changzhou as non-residence)	—	0.0027***	—	—
	—	(0.0006)	—	—
Su Shi’s stay	—	—	0.0020***	0.0065**
Su Shi’s stay	—	—	(0.0006)	(0.0030)
Observations	257	257	257	169
R-squared	0.4710	0.4705	0.3846	0.6414

Notes: Robust standard errors are in parentheses; ** and *** denote the significance level of 5% and 1%, respectively; controls are the same as those in column (4) of Table 2.

It is also noted that Su Shi only resided in some cities for a month or two. For example, Su Shi was appointed as an official of Dengzhou (now a district in Yantai) but only stayed there for about half a month because of a new appointment five days later. Su Shi’s stay in Changzhou, where Su Shi chose to reside and died, was also very short, less than two months. One may argue that these stays could be too short to allow the poet to produce a substantial effect on local society and thus on city tourism nowadays. To address this concern, we treat both cities as without Su Shi’s residence in a new variable and report the regression result in column (2). It shows that one month’s stay is also related to an increase in domestic tourism revenue of 0.27%, almost the same as the main result.

We also use domestic tourist arrivals as the city tourism outcome. If Su Shi’s residence increases tourism revenue, it should also attract visitors. As expected, we find from column (3) that his stay also increases domestic tourist arrivals by 0.2%, a slightly smaller effect than that on tourism revenue. We finally use real terms of tourism revenue and GDP per capita at the 1999 price level. As a result of many missing values in city CPI, the observations sharply reduce to 169. But column (4) shows that Su Shi’s stay still has a tourism promotion effect. Now the estimate is 0.0065. Therefore, our main results are highly consistent under alternative measures of both variables of interest.

Changing observations

The second set of robustness exercises changes the observations used. It first uses observations including provincial capitals. It is noted that excluding provincial capitals also removes two important cities that Su Shi resided in for long periods. The first city is Hangzhou, where Su Shi worked twice. The second city is Haikou, which we use to replace Danzhou as his last place of exile because of a lack of statistics on tourism in Danzhou. The regression result with all 284 prefectural-level cities is presented in column (1) of Table 4, which shows that Su Shi’s stay still contributes positively to domestic tourism revenue. The estimate is 0.0019, smaller than the main result with observations from non-provincial capitals and non-megacities.

Table 4.

Robustness checks by changing observations.

Variable	(1)	(2)	(3)	(4)
	Including provincial capitals	Territory in the Northern Song Dynasty	Removing Kaifeng, the capital	Removing cities where Su Shi visited
	Ln (domestic tourism revenue)
Su Shi’s stay	0.0019***	0.0029***	0.0030***	0.0026***
Su Shi’s stay	(0.0007)	(0.0007)	(0.0008)	(0.0008)
Observations	284	206	256	203
R-squared	0.5076	0.4761	0.4697	0.4741

Notes: Robust standard errors are in parentheses; *** denotes the significance level of 1%; controls are the same as those in column (4) of Table 2.

This result suggests that Su Shi’s stay had a much smaller tourism effect in large, central cities because Su Shi added little to tourism resources in these cities. For example, Hangzhou was an economic, political, and cultural center in the Song Dynasty. Other historical celebrities had left their relics in this city. One example is Bai Juyi, a great poet in the Tang Dynasty (618–907). Bai Juyi spent his youth in Hangzhou and returned there in October 822 A.D., 250 years before Su Shi’s first arrival, as a governor for about two years. He also had excellent governance performance in Hangzhou and composed about 200 poems regarding Hangzhou. In memory of his contribution to this city, the first causeway in the beautiful West Lake was named after him, that is, Bai Causeway. Therefore, Su Shi may have a much smaller effect on tourism in regional central cities like Hangzhou.⁶

We also confine the data within the map of the Northern Song Dynasty. Peripheral areas and provinces such as Northeastern China, Inner Mongolia, Xinjiang, Ningxia, Tibet, and Yunnan were territories of minority regimes at the time. Thus, we remove the data from these provinces and re-estimate the effect of Su Shi’s residence. Again, from column (2), we find that Su Shi’s stay promotes city tourism today with a slightly larger estimate than that in column (4) of Table 2.

We then remove the capital of the Northern Song Dynasty, Kaifeng. Su Shi spent over 11 years there serving as a central government official. As a result, Kaifeng is the second-longest city of his residence following his stay in his homeland, Meizhou. However, Su Shi had limited room to influence daily lives in the capital and leave traces for tourism development nowadays. As a capital, Kaifeng must have a lot of historical sites. However, the city was repeatedly flooded by the Yellow River. Consequently, rarely have tangible relics of historical celebrities before the Ming Dynasty been preserved. Nevertheless, given that Kaifeng is an ancient top tourist city, including it may overstate the tourism effect of Su Shi. To alleviate this concern, we remove Kaifeng from our estimation and report the regression result in column (3) of Table 4. It reveals that Su Shi’s stay still increases domestic tourism revenue but by a slightly greater estimate of 0.003, suggesting that the effect is not overestimated by including the former capital.

Finally, we consider Su Shi’s traveling stops where he composed poems. It has been documented that Su Shi traveled across 482 places, with some repeated arrivals. According to our calculation with the data from Wang (2017), these travels involved 80 prefectural and above-level cities today (see also Figure 1). Since Su Shi may also add cultural heritage to cities without his residence but only with his arrival, including these cities as unaffected by Su Shi would underestimate the tourism impact of Su Shi. We thus remove the 80 cities and re-estimate equation (1). Column (4) of Table 4 reports the regression result, showing that one month’s stay is associated with an increase in tourism income by 0.26%, a magnitude slightly smaller than that in Table 2.⁷ Therefore, our main result is not driven by treating these stops as without his residence.

Including more controls

We then include some more controls that may determine domestic tourism revenue. This can hopefully raise the estimation precision on the effect of Su Shi’s stay since it is unlikely that these determinants can affect his stay. Specifically, we first add public expenditure per capita, the share of tertiary industry in GDP, and the number of four-As grade tourist attractions (4ATAs) to the right side of equation (1). Previous studies have also used these variables to explain city tourism (Gao et al., 2020; Gao and Su, 2019). However, results in column (1) of Table 5 show that adding these controls increases standard errors, leads to a smaller estimate, and thus reduces the estimation precision. This may imply that variables such as the number of 4ATAs could channel the effect of Su Shi’s residence, which we will test in the the channel analysis . In column (2), we further control provincial dummies and find a positive effect of Su Shi’s stay. However, because these dummies absorb variations in Su Shi’s stay, the estimate reduces to 0.0016 but remains significant at 5%.

Table 5.

More controls, matching, and falsification tests.

Variable	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	Adding More controls			Matched cities		Falsification test
	Ln (domestic tourism revenue)					Ln (1+inbound tourism revenue)	Ln (1+inbound tourist arrivals)
Su Shi’s stay months	0.0020**	0.0016**	0.0021***	—	0.0030*	−0.0015	0.0025
Su Shi’s stay months	(0.0009)	(0.0007)	(0.0008)	—	(0.0015)	(0.0046)	(0.0034)
Classical works before Su Shi's birth	—	—	0.0894***	—	—	—	—
Classical works before Su Shi's birth	—	—	(0.0252)	—	—	—	—
Su Shi’s stay dummy	—	—		0.4323**	—	—	—
Su Shi’s stay dummy	—	—		(0.1701)	—	—	—
Observations	257	247	257	34	34	254	254
R-squared	0.6368	0.8368	0.4895	0.8179	0.7958	0.4889	0.5911

Notes: Robust standard errors are in parentheses; *, **, and *** denote the significance level of 10%, 5%, and 1%, respectively; additional controls in column (1) are public expenditure per capita, the share of tertiary industry, and the number of 4ATAs; column (2) further includes provincial dummies; other controls are the same as those in column (4) of Table 2.

Finally, we try to control the cultural heritage across cities before Su Shi. One may argue that Su Shi’s stay is not exogenous, although the imperial court determined most of the places he resided. When he was out of favor with his political enemies, he was exiled to a remote place with less cultural heritage; when the emperor favored the poet, he would be appointed to be a governor of wealthy cities such as Hangzhou. These selection behaviors would bias our estimation since they are related to cultural heritage in cities where Su Shi resided, which further determines city tourism today.

To address this concern, we use the number of Classical Chinese works finished in each city by literati born before Su Shi during the Tang and North Song Dynasties to measure the abundance of cultural heritage in each city before Su Shi’s arrival. We took the data from Wang (2017) by confining the birth year of the literati between 580 A.D. and 1035, the year before Su Shi’s birth. Column (3) of Table 5 presents the result controlling for the natural logarithm of city cultural heritage ahead of Su Shi’s birth. Again, we find that Su Shi’s stay has a statistically significant effect on domestic tourism revenue, with an estimate of 0.0021. The number of classical works is positively associated with current city tourism revenue, with an elasticity of 0.0894. These results suggest that potential selections in Su Shi’s residence will slightly overestimate the tourism value of Su Shi’s residence but do not undermine our main result.⁸

Results from matched data

While the existing literature broadly uses the observable variables to determine matched cities of treated ones as done by the propensity score matching method (Abadie and Imbens, 2016), it is questionable here to match cities without Su Shi’s stay to where he resided in terms of observed variables nowadays. Cities matched with observable characteristics today may fundamentally differ in other dimensions such as locations and in unobservable aspects in the Northern Song Dynasty. For example, the sub-national administrations (“Lu,” similar to province) are different from provinces nowadays. There were 24 Lus in the Northern Song Dynasty, consisting of 254 prefectures.⁹

To make cities with and without Su Shi’s residence more comparable, we use historical information and the distance of cities to the capital at the time, Kaifeng. Specifically, we first draw a circle with the capital as the center and the distance of each city with Su Shi’s residence to the capital as the radius. We then draw a 100 km-wide belt area along the circle in the Lu where the cities with Su Shi’s residence are located. If a city’s coordinate location falls in the belt area, we will count it as a matched one. These cities are similar to cities with Su Shi’s residence because they are geographically adjacent, located in the same Lu, and have a similar coordinate distance to the power center, Kaifeng city. As a result, we attain 26 matched cities of those with Su Shi’s residency (see online Appendix Table A4 for detailed matching information). Among these matched cities, two cities where Su Shi resided are also other cities’ matched ones, and one city is the provincial capital. Since we mainly use non-provincial capital cities, we finally get data including 14 cities where Su Shi resided and 20 matched cities. Columns (4) and (5) of Table 5 report regression results. Again, we find that cities where Su Shi stayed have larger domestic tourism revenue today. The estimations are less precise because of 34 observations in total.

Falsification tests

While Su Shi is one of the most influential cultural celebrities in the Chinese circle, people from other countries may find it difficult to appreciate his poems and essays written in Classical Chinese. This is a salient feature of cultural and heritage tourism differing from tourism related to landscapes. People with distinct cultural backgrounds can appreciate breathtaking landscapes, but they may have limited interest in visiting a place with cultural heritage that they find hard to understand. Moreover, cultural familiarity can shape a country’s good image (Choi et al., 2020) and increase the intention of tourists to visit a destination (Lee et al., 2008). Thus, in contrast to the positive effect on domestic tourism, Su Shi’s residence should have a negligible or insignificant effect on inbound tourism. To check this, we estimate its impact on inbound tourism revenue and tourist arrivals. Regression results in columns (6) and (7) of Table 5 confirm that Su Shi’s stay has an insignificant effect on both inbound tourism outcomes.

Channels

We further test two potential channels to safeguard the tourism promotion effect of Su Shi’s residence. First, tourism stakeholders can use Su Shi’s relics and cultural heritage to develop local tourism industries and thus increase their tourism revenue. We capture the first channel with current tourism development variables such as the number of high-level tourist attractions, the number of World Heritage Sites, and TTC designation status. Second, Su Shi’s residence resulted in the later accumulation of cultural heritage. As a very influential celebrity over the decades, Su Shi motivated later literati to follow his footprints and compose verses there. He also inspired generations of youth in cities with his residence to study hard and become talents of the palace or celebrities. Accumulated local cultural heritage forms these cities’ advantages over other cities in terms of historical and cultural resources available for tourism purposes.

Indeed, Su Shi’s relics and heritages have become several famous tourist attractions and sites in the cities he dwelled. For example, Su Shi’s former residence in his hometown Meizhou has become a 4ATA to memorize him, his father, and his brother. Owing to his first exile in Huangzhou, the local government developed another 4ATA, Dongpo Chibi. In Hangzhou, where Su Shi served as a governor twice, the West Lake, which includes several sites related to him, was inscribed as a WHS in June 2011. One of the two causeways, which was Su causeway, built under his governance and named after his surname, has long been crowded with tourists. Even in Dengzhou, where Su Shi stayed only about half a month, a temple was built to memorize him and attract tourists. According to our incomplete collections, Su Shi’s relics and heritages have contributed to the designations of one WHS, three 5ATAs, two 4ATAs, two 3ATAs, and dozens of tourist sites such as memorial halls, academies, temples, and landmarks (for details, see online Appendix Table A1).

To test the first channel formally, we estimate the impact of Su Shi’s stay on the number of 5ATAs, the number of 4ATAs, the number of WHSs, and the TTC designation, all of which are the means between 2002 and 2019. We further control public expenditure because gaining those designations requires large-size public spending. Regression results are reported in Table 6. We find that his residence tends to increase the number of 5ATAs and 4ATAs (see columns (2) and (4)). Cities where Su Shi stayed have 0.32 more 5ATAs and 2.71 more 4 ATAs than those where he did not, although the effect on the number of 5ATAs is marginally significant. However, Su Shi’s stay has no significant effect on the number of WHSs and the TTC designation (see columns (5)–(8)). The distinct effects on high-level tourist attractions and other forms of designations may lie in the fact that Su Shi’s relics in a city are not large enough to determine the designation of a TTC, and they are not properties with universal values that a WHS designation requires. Nevertheless, these positive effects of having Su Shi’s stay on the number of 5ATAs and 4ATAs confirm that Su Shi’s residence can facilitate the development of tourist attractions today.

Table 6.

The impact of Su Shi’s residence on current tourism development.

Variable	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
Variable	Number of 5ATAs		Number of 4ATAs		Number of WHSs		Top tourist city designation
Su Shi’s stay months	−0.0000	—	0.0066	—	0.0008	—	−0.0003	—
Su Shi’s stay months	(0.0007)	—	(0.0080)	—	(0.0027)	—	(0.0002)	—
Su Shi’s stay dummy	—	0.3199*	—	2.7093***	—	0.1242	—	0.0291
Su Shi’s stay dummy	—	(0.1659)	—	(0.7281)	—	(0.1866)	—	(0.1001)
Observations	257	257	257	257	257	257	257	257
R-squared	0.1149	0.1324	0.1399	0.1730	0.1181	0.1193	0.1461	0.1330

Notes: Robust standard errors are in parentheses; *** denotes the significance level of 1%. Controls include GDP per capita, population density, public expenditures, and regional dummies regarding western, central, and coastal areas.

The second channel proposes that Su Shi having resided in a city can increase later cultural heritage. We test it in two ways. First, we use the number of Classical Chinese works, which includes poems (shi), lyrics (ci), descriptive poetry (fu), and essays (wen), in the Song Dynasty to measure a city’s cultural heritage. To guarantee that these works could be motivated by Su Shi, we confine it to those works written in the years after his decease, that is, from 1102 to 1250. The data are taken from the webpage based on the data by Wang (2017) (see online Appendix Table A3). Columns (1)–(2) of Table 7 report regression results regarding the effect of Su Shi’s residence on classical works by later literati in the Song Dynasties after his death. It is shown that Su Shi’s longer stays are associated with more classical works by later literati, which also holds for the extensive margin. One more month’s stay will increase the number of classical works in his residence city by 0.94% (see column (1)), and cities where Su Shi stayed have 1.015 times more classical works than those without his stay (see column (2)).

We then use the number of Jinshi in each city during the Qing Dynasty (1636–1912) to measure the density of cultural heritage. The data are manually collected from Jiang (2007) which contains the most comprehensive information on Jinshi between 1646, the third year of the Qing Empire’s rule in China, and 1904 when the last palace examination was held. City-level Jinshi numbers are constructed by counting the number of Jinshi in each city according to their homelands. Estimation results presented in columns (3) and (4) of Table 7 show that Su Shi’s stay is positively associated with the number of Jinshi during the Qing Dynasty, which is more significant for the extensive margin. Cities where Su Shi stayed had 96% more Jinshi during the Qing Dynasty.

In columns (5) and (6) of Table 7, we further report test results on the effect of both channel variables regarding cultural heritage in promoting city tourism nowadays. They show that a 1% increase in the number of classical works during the Song Dynasties after Su Shi’s decease is associated with an increase in domestic tourism revenue of about 0.11% (see column (5)). Meanwhile, a 1% increase in the number of Jinshi in the Qing Dynasty is associated with an increase in domestic tourism revenue by 0.165% (see column (6)). Both effects are statistically significant at the 1% level. Therefore, the channel analysis confirms the long-run effect of Su Shi on modern city tourism by showing that his residence facilitates tourism development today and induced later literati to create more cultural heritage in the places where he stayed.

Table 7.

The effect of Su Shi’s residence on cultural heritage in a city.

Variable	(1)	(2)	(3)	(4)	(5)	(6)
Variable	Ln (1+no. of classical works)		Ln (1+no. of Jinshi in the Qing Dynasty)		Ln (domestic tourism revenue)
Su Shi’s stay months	0.0094*	—	0.0036	—	—	—
Su Shi’s stay months	(0.0051)	—	(0.0030)	—	—	—
Su Shi’s stay dummy	—	1.0153**	—	0.9600***	—	—
Su Shi’s stay dummy	—	(0.4370)	—	(0.3288)	—	—
Ln (1+no. of classical works)	—	—	—	—	0.1062***	—
Ln (1+no. of classical works)	—	—	—	—	(0.0209)	—
Ln (1+no. of Jinshi)	—	—	—	—	—	0.1653***
Ln (1+no. of Jinshi)	—	—	—	—	—	(0.0341)
Observations	257	257	257	257	257	257
R-squared	0.4718	0.4753	0.4381	0.4511	0.5017	0.5130

Notes: Robust standard errors are in parentheses; *, **, and *** denote the significance level of 10%, 5% and 1%, respectively; controls in columns (1) to (4) are provincial dummies; controls in columns (5) and (6) are the same as those in column (4) of Table 2.

Conclusion and discussion

This paper uses one of the most influential cultural celebrities of ancient China, Su Shi, as a case study to estimate the long-run tourism effect of historical celebrities. Functioning similarly to the roles of modern stars in tourism, historical celebrities can enhance the place engagement and attachment of tourists, based on which local tourism can be advertised and developed. In addition, historical celebrities facilitate tourism development based on their relics and the local cultural heritage of later literati motivated by their residence. As a result, prominent historical celebrities have substantial place-based tourism value today.

Using Su Shi as a case to estimate the tourism effect of historical celebrities, we find that an additional month of his stay will increase the average domestic tourism revenue between 2002 and 2019 by about 0.3%. The positive effect is consistent under many robustness checks, including using alternative measures of Su Shi’s residence and city tourism outcomes, changing observations and adding more controls to alleviate the endogeneity concern, using matched data based on geographical and historical information, and conducting falsification tests with inbound tourism variables. We also document that the tourism promotion effect is driven by tourism development based on relics of his residences and by the subsequent accumulation of cultural heritages motivated by him.

Several theoretical implications can be developed from our findings. A positive effect suggests that the celebrity-tourism links also hold for historical literatus. We thus broaden the celebrity-induced tourism literature (Glover, 2009; Xu and Pratt, 2018) by extending it to historical celebrities and examining the long-run effect. While a film celebrity may enhance tourism by endorsing destination and attracting fans, influential historical celebrities like Su Shi also induce later accumulation of cultural heritages and enable the development of tourist attractions based on their relics. Since Su Shi is one of the most influential literatus, our work also demonstrates the critical roles of local cultural heritages in tourism development, thereby adding to the literature regarding the place-based cultural tourism development (Backman and Nilsson, 2018; Smith, 2015; Van Loon et al., 2014). It displays the power of cultures and heritages created and enlightened by outstanding historical figures in shaping a city’s tourism attractiveness. Specifically, historical celebrities increase local tourism supply by adding unique tourism resources, which in turn can meet the demand of domestic tourists for them. Therefore, our results integrate theories regarding mixed nexuses in the roles of both celebrities and cultures in developing city tourism economies. We disclose that historical celebrities can influence today’s tourism through their power in nurturing and accumulating local cultural heritages which can be tangible through their relics and memorials.

Our findings also have some practical implications for local tourism development. A long-run tourism promotion effect of Su Shi suggests that city tourism can gain persistently from historical celebrities through developing tourist attractions and sites based on relics and cultural heritage related to them. This calls for proper preservation and protection of celebrity-related relics and heritages to provide visitors with an authentic experience. Meanwhile, local tourism administrations should balance tourism development and heritage protection to make the historical celebrity-induced and place-based tourism sustainable, as argued in the literature linking WHS to tourism (Drost, 1996; Gao and Su, 2019; Zhang et al., 2015). While a historical celebrity can serve as a valuable city icon for tourism marketing, over-tourism should be prohibited since it would place precious relics and heritages under threat and worsen tourists’ visiting experience.

However, it is also worth noting that the tourism values of historical celebrities should not be overstated since our estimation is based on, perhaps, the most influential and famous cultural celebrity in ancient China since the Song Dynasty. Other celebrities may also have some but much less tourism value than Su Shi because they are mostly memorialized in one or two places, such as their former residence, and have a much less pervasive tourism effect. Tourist attractions based on them may not attract as many tourist arrivals as those based on Su Shi due to their lower popularity and small fame. Therefore, our case study cannot be simply extended to predict the tourism value of other historical celebrities, and tourism development based on less influential celebrities should be cautious and requires more careful evaluations. Another limitation is that we do not test how tourists would perceive and respond differently to tourist attractions with and without the residence of an influential historical celebrity. While this channel can be rationalized from the above-mentioned literature regarding the tourism effect of modern celebrities, it is worth exploring by future studies with survey data. Despite these limitations, we provide the first evaluation of the long-run tourism effect of Su Shi which can be extended to study other historical celebrities and cultural heritages.

Supplemental Material

Supplemental Material - The long-run tourism effect of historical celebrities: Evidence from one of China’s most influential literatus in China

Supplemental Material for The long-run tourism effect of historical celebrities: Evidence from one of China’s most influential literatus in China by Yanyan Gao and Wei Su in Tourism Economics

Footnotes

Acknowledgment

The authors thank Professor Gang Li at University of Surrey and Yu Zhang at Nanjing Audit University for their valuable comments, Miss Lin Zhang at Southeast University for her excellent research assistance, and Doctor Fan Yang at Southeast University for kindly sharing the data of Jinshi in the Qing Dynasty.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Jiangsu Social Science Foundation (Grant no. 20EYB003).

ORCID iD

Yanyan Gao

Supplemental Material

Supplemental material for this article is available online.

Notes

Author biographies

Yanyan Gao is Associate Professor at the School of Economics and Management, Southeast University, China. His research interests involve multiple applied economics topics regarding tourism, innovation, and transportation infrastructures, using causal inference methods such as difference in differences, instrument variables, and regression discontinuity design. Dr. Gao has published widely in peer-reviewed leading journals such as World Development, Tourism Management, Research Policy, Annals of Tourism Research, Journal of Travel Research, and Energy Policy.

Wei Su is Associate Professor and the dean of the School of Hospitality Management, Nanjing Institute of Tourism and Hospitality, Nanjing, China. Her research fields are tourism development and hospitality management. Her research works appear in peer-reviewed leading journals like Tourism Management, Annals of Tourism Research, and Journal of Travel Research, and she has hosted several research projects on evaluating the roles of cultural heritage in local tourism development.

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