Do Tourists Care About Old Buildings?

On the surface, this seems like a trivial question. When we look at international tourism flows, Paris stands at the top for a reason, with 30 million annual tourist visits. Why would millions of people from around the world travel to see this particular city? Not only that, it’s not the entire city of Paris that most tourists come and see, but rather the comparatively small inner “old-town” portion of the city. In this anecdote, it’s evident that the old buildings of Paris play an essential role in attracting tourists.

In this article, I want to explore historical architecture as a potential tool for determining if a destination is over or underrated. So naturally, if old buildings play an essential role in Paris tourism, maybe we can generalize to other cities.

For most people worldwide, tourist travel remains a luxury good that often symbolizes status and wealth. As a good for conspicuous consumption, tourism relies heavily on easily “Instagrammable” locations that an audience would quickly recognize and associate with specific traits (Kock 2021, Bronner & de Hoog 2018). The Eifel Tower might be associated with wealth and sophistication, or the St Peter’s Square in the Vatican with spiritual dedication. 

It’s clear that there is a strong relationship between Instagram and various tourism measures. However, the association is endogenous and challenging to model with econometrics. Surveys are still the best way to quantify travel motivations. Despite the weaknesses in surveys, these studies tell us more or less the same story: social media is king (Taylor 2020, Kock 2021, Liu et al. 2019). Social media makes it easy to find the most effective signal per dollar spent on travel.

Authenticity as a Status Signal

Here, the age of the building is irrelevant if it does not play a role in the signaling process. Many of the “old buildings” we see in many European cities are not old but rather reconstructions or modern interpretations of historic architecture. This consideration hardly bothers most tourists, who will never question the age of the Eifel Tower. However, the old or old-looking buildings provide authenticity to the Instagram backdrop. They make the location somehow seem worthy of the time and money spent.

The literature is somewhat suspect on this account. Both the papers Mariani and Guizzardi (2020) and Ribaudo and Figini (2017) show that the UNESCO World Heritage designation has an ambiguous or no effect on tourist flows. However, UNESCO sites are often in remote locations or are focused on arcane historical events. Several other papers using survey data suggest a minor impact of local architecture on the decision to travel (Turner 2017, Ramkissoon & Uysal 2011, Genc 2017)

From a policy perspective, understanding the importance of “old buildings” or a visual identity more generally can help manage the difficulties of mass tourism. I hypothesize that old buildings can encourage tourism by creating a monumental selfie backdrop or indirectly establishing an authentic atmosphere for Instagram photos. (e.g., as in Chi & Chi 2022) Establishing “new authentic” destinations can relieve pressure on overburdened locations. For the individual seeking authenticity, it can also help guide you to the best destinations.

For a deep dive into the theory of tourist authenticity, check out my overview here:

The German Cataclysm

Germany provides an interesting case study to shed light on the question. During the Second World War, Allied Bombing raids simply removed German cities from existence. Of the ten largest cities, only one had less than 50% of its housing stock destroyed, and none had any significant portion of the historic city center survive. In most cases, cities rebuilt their center with wider avenues for cars and modernist housing blocks, removing any historical continuity in the cityscape.

However, German cities remain enduring tourist attractions, including Cologne and Frankfurt, which were described as among the “most destroyed cities in Europe” after the war. In addition, several significant cities survived the war comparatively better off, such as Leipzig and Munich. This variance in the number of old buildings might give us a window into the variance we see in tourist flows between these cities.

The Data

I assembled a small dataset across 98 of Germany’s independent municipalities. Each city refers to a county-level administrative entity, so we have consistent measurements across each variable.

There are two readily available options for counting old buildings, and both have fundamental flaws. The first statistic is the percentage of the pre-war housing stock destroyed by the war’s end. Cities had to decide which buildings could be saved and which were total losses. In general, every region did things differently, with Bavaria writing off buildings at least 50% damaged but other regions requiring 80% damage for a total loss. Sometimes untouched buildings were torn down, and sometimes total losses were restored.

What if it’s not the quantity but the quality of old buildings that generates authenticity? This “instagrammability” of a city is difficult to capture. To help, the German government also provides geotagged “monuments” such as UNESCO World Heritage Sites and other famous places such as the Valhalla in Bavaria. I use QGIS to map these sites to their geographic entity and report a count. So, e.g. Berlin has seven, and Trier has one. This statistic may be a proxy for a “dramatic selfie backdrop.”

The second statistic is the modern-day audit of buildings with a title that predates 1945. The German statistical authority Destatis collects this information, and there is no reason to doubt the consistency of the numbers. However, modern cities are much larger than in 1945, and the percentage of old buildings today reflects population growth and not the number of heritage sites.

Both statistics suffer from the fact that total housing stock is not a direct proxy for the historical architecture that tourists care about. I suspect cities with more pre-war housing stock will correlate with a better-preserved city center. I divided the number of old buildings by the city’s population to get a more standardized measure.

The dependent variables of interest are two statistics relating to tourism. The first is Instagram Posts per Capita, which I gathered using the Instagram API. The second is the number of overnight stays per capita taken from the Destatis database. Both are calculated per capita to reduce the effect of population on the statistics, i.e., larger cities will have more Instagram posts.

For an overview of the other statistics, see the article on the data I am using.

The Results

It’s clear from the preliminary data analysis that the relationship between tourists and old buildings is tenuous at best. A very simple linear regression with heteroskedasticity corrected standard errors shows no meaningful relationship. From this point, I think the answer to this question is pretty definitive: old buildings do not impact overall travel within this dataset.

There are other interesting points to consider, though, as I move towards creating a broader tourism score. In the base model, overnight stays are so effectively explained by the number of hotel rooms that any other variable is tangential at best. The counterpart using the level of wartime destruction versus overnight stays seems to have uncovered more interesting relationships between the variables. However, the effect of hotels on the target variable is still the dominant one.

Using Instagram posts per city tag offer a more exciting set of results. The first point is the significant and positive impact that GDP per Capita has on the number of Instagram posts. This result is not surprising since conspicuous travelers may be more interested in consuming expensive products. Such luxury products are probably more readily available in locations with more money.

Likewise, as was the initial hypothesis for Instagram posts, the presence of famous monuments suggests more posts per capita. The value is significant in both models and supports the theory that only certain old buildings offer value to tourists.

Likewise, there is a strong negative correlation between old buildings and the GPD per Capita and capital cities. This indicates that any potential hidden gems are likely to be smaller provincial cities. Further anecdotal evidence supports this, with famous UNESCO Heritage cities such as Bamberg, Heidelberg, and Weimar appearing to have more overnights and Instagram posts than the average.

The German office of statistics also breaks overnight stays into several categories, including the origin of the tourist, either foreign or domestic. I ran the model for both types, and the results for foreign tourists are also interesting.

While the effect of wartime destruction and old buildings remains insignificant, the impact of tourist momentum on specific monuments in the cities becomes relevant. These variables suggest that my hypothesis regarding tourist flow may apply only to foreign tourists rather than domestic ones.


The results here suggest that old towns are not that important in attracting tourists, though there may be certain exceptions. These exceptions may include the presence of recognizable monuments that signal specific values to certain audiences. Alternatively, old towns may drive tourism to particular subsets of tourists for which we do not have data. In any case, they do not register in the dataset that I have available.

The next step would be to analyze the Instagram pictures in more detail. I could, for example, check if a historical building was in the background and use this information to see if it impacts travel. An alternative approach would measure intent to travel rather than actual travel, e.g., Google Trends for “Berlin Hotel.” Or I could determine if specific historical monuments are responsible for the travel intention. However, all of this requires difficult-to-obtain or subjective data.

Another confounding factor, returning to the idea of “New Authentic” places, is the reconstructed old towns in cities like Dresden and Frankfurt, particularly as a potential motivator for tourist travel. These will not appear in the statistics I have, but they still fulfill the role of creating authenticity. More generally, some measure of authenticity may be needed going forward.

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Chi, O. H., & Chi, C. G. (2022). Reminiscing Other People’s Memories: Conceptualizing and Measuring Vicarious Nostalgia Evoked by Heritage Tourism. Journal of Travel Research, 61(1), 33–49.

Kock, F. (2021). What makes a city cool? Understanding destination coolness and its implications for tourism. Tourism Management86, 104317.

Genc R. 2017. “Value Creation through Heritage and Identity.” In Co-creation in Tourist Experiences, edited by Prebensen N. K., Chen J. S., Uysal M. S., 50–63. London: Routledge.

Liu H., Wu L., Li X. 2019. “Social Media Envy: How Experience Sharing on Social Networking Sites Drives Millennials’ Aspirational Tourism Consumption.” Journal of Travel Research 58 (3): 355–69.

Mariani, M. M., & Guizzardi, A. (2020). Does Designation as a UNESCO World Heritage Site Influence Tourist Evaluation of a Local Destination? Journal of Travel Research, 59(1), 22–36.

Ramkissoon H., Uysal M. S. 2011. “The Effects of Perceived Authenticity, Information Search Behavior, Motivation and Destination Imagery on Cultural Behavioral Intentions of Tourists.” Current Issues in Tourism 14 (6): 537–62.

Ribaudo, G., & Figini, P. (2017). The Puzzle of Tourism Demand at Destinations Hosting UNESCO World Heritage Sites: An Analysis of Tourism Flows for Italy. Journal of Travel Research, 56(4), 521–542.

Taylor D. G. 2020. “Putting the ‘Self’ in Selfies: How Narcissism, Envy, and Self-Promotion Motivate Sharing of Travel Photos through Social Media.” Journal of Travel & Tourism Marketing 37 (1): 64–77.

Turner, B. S. (2017). The Authenticity of Heritage Sites, Tourists’ Quest for Existential Authenticity, and Destination Loyalty. Sociology, 56(8), 189–217.

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