Category Archives: Tourism Forecast

What Extent We Can Rely on Tourism Forecast?

By Dripto Mukhopadhyay

In research fraternity, forecasting is always known as “Thankless Job”. The reason being it is one of the most difficult exercise since forecasts depends on large number of assumption about future over and above the assumptions involved in the econometric modelling itself. Being fortunate enough to work on forecasting relating to various sectors ranging from petroleum demand to luxury car to carbon emission, I know the amount of effort and skill goes behind any forecasting exercise, if it is a serious business. Even after that, many of the times the researcher find their forecasts off the target extensively mostly because of externalities. At times I feel that except a “Fortune Teller”, no scientific researcher ever can guarantee about the forecasts. The forecasts can change drastically because of small amount of change in any of the multiple assumptions goes into forecast because of macro-scenario in a dynamic world.

However, a researcher always wants to understand how his forecasts are matched with actual scenario after a few years of the forecasts were made. I did a forecasting for foreign tourists arrivals to India in the year 2008-09 for Indian Institute of Tourism and Travel Management (IITTM) as a consultant. The paper was published later in the “Indian Tourism Statistics”, the only government publication on tourism statistics of India. The forecasts were made from 2010 to 2014. Since recently the latest Tourism Statistics published for the year 2015 contains data for 2014, I felt like matching the accuracy of the forecasts I made in 2008.

The research paper covered 6 countries and all the regions of the world. The data used was various macro economic parameters, household disposable income and certain dummy variables relating to policy and other localised incidences like terrorism etc. The comparison between forecasts made in the year 2008 and the actual foreign tourists arrival to India. The details of the accuracy level of the forecasts is given in Table 1. Country-wise details and region-wise details are given in Table 2.

For any secondary data collected in a large scale and at a macro level, it is always considered that results are extremely accurate if lies within plus/minus 10% deviation level. An accuracy level till 85% (where the deviation is plus/minus 15%) is considered as acceptable for any valid decision making purpose. The numbers presented in Table 1 provides the details of forecast numbers from 2010 to 2014 for all countries and regions covered under the study. It suggests that 62% forecast numbers in the study is extremely accurate when compared with the actual FTA (Foreign Tourist Arrival). If we consider the acceptable limit with 85% accuracy, it goes up to 77% of the forecasted data points. Overall, this results suggest that FTA forecasts made in 2008 was fit to the expectations out of any forecasting exercise. Keeping in mind the global economic recession during end of 2008 and the continuing volatility of the global economy, these results suggests that decision making and policy making can depend on forecasts to a large extent if the methodology used is robust.

Table 1: Details of Accuracy Level of Forecasts

(Forecasts made in Year 2008 for the years 2010 to 2014)

Forecast VS Actuals

Accuracy level

% Forecast points

On target 100% correct

34

Highly accurate More than 90% accuracy

28

Acceptable Accuracy level 85% to 90%

15

Low on accuracy Accuracy level less than 85%

23

Table 2: Regions and Country of Details of Forecasts and Deviation of Actual Foreign Tourists Arrivals to India

forecast summary

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Tourism Scenario in India – Some Revelations

In the previous blog I wrote about foreign tourists arrivals to india and some critical concerns about those. In this blog I have shown a more complete picture regarding Indian tourism scenario, including both domestic and international, and its spatial impolications. To make this blog more reader friendly I have given more visual impressions and tried to lessen the burden of text. The latest complete data available on Indian tourism is for the year 2012. Thus, the article talked about 2012 scenario only.

In Figure 1 exhibits number of domestic tourists, foreign tourists and total tourists travelled to different Indian states. If we look carefully at the graph, we find that:

1. Toruists visits are largely concentrated in a 5/6 states. These states are Andhra Pradesh, Tamil Nadu, Uttar Pradesh, karnataka and Tamil Nadu – the top 5 states in terms of total toruists arrivals.

1

Figure 2 shows the distribution of domestic tourists and total tourists in Indian states. As seen in previous figure, the share shows that about 65% of the total tourists travel to these 5 states. The top ranking state is Andhra Pradesh, which accounts for 20% of the tourists. Continue reading

Foreign Tourists Arrivals to India Reflecting Global Economic Recovery Now

Inbound tourism to India experienced the impact of global economic recession severely starting last quarter of 2008. Though Indian economy apparently showed signs of early recovery towards the end of 2009, other countries were still fighting on how to grapple with recession. However, apart from some of the European countries and Asian countries like Japan, gradually the situation improved towards betterment. Though the countries were still struggling with slow GDP growth, unemployment and other crucial economic indicators, most of the countries started gaining the growth momentum, slowly but steadily.

Indian tourism industry that saw a significant change since beginning of the decade 2000 was hit dearly because of the global economic recession. A sudden dip was observed in inbound tourists to India. And, this was true for every originating country where from tourists visited India. It was expected that the scenario should start changing in a year or two. This was especially true from the perspective of various stakeholders within tourism industry, especially the core ones like hotels, tour operators etc. The hotel prices were slashed significantly with various discounts and incentives on face of recession coupled with fierce competition because of entry of new international as well as smaller domestic players.

However, the scenario did not turn like that. Though economies started moving upwards in most of the countries, especially the developed ones, the impacts were not felt instantly. Anyone worked on tourism demand forecasting for inbound tourists knows that two crucial variables explain substantial part of data variation in tourists’ arrivals to any country. These are income in the originating country (expressed in terms of GDP) and lag of tourist arrivals, i.e., the number of tourists arrived during previous year or so. All other parameters like cost comparison, distance to travel, law and order including terrorist activities etc. do play their role, but to a much lesser extent. But this time, the demand system behaved in a slightly different manner. There was a lag effect that played a crucial role in the system. Increase in income in the originating countries did not show its influence immediately. A look at the data will ensure the explanation in a meaningful manner.

Table 1: Foreign Tourist Arrivals (FTA) in ‘000
 Month 2009 2010 2011 2012 2013 2014
Jan 481 569 624 681 699 720
Feb 490 552 636 677 688 738
Mar 442 512 550 623 640 669
Apr 348 372 438 452 452 504
May 305 332 355 372 384 421
Jun 352 385 412 432 444 492

We find two important points from Table 1 as given above. The data is given for first 6 months of each year starting from 2009 so that no confusion is created regarding the trend. Primarily this is because of the fact that data for 2014 is available till the month of June. So, data for rest of the months for other years may create a noise in the pattern where 2014 data plays a crucial role. The second important reason is Indian tourism is marked with significant periodicity or seasonality which I have mentioned in several of my previous blogs as well as have been clearly established by many research papers. Inclusion of data for other years and not for 2014, may create a problem to identify the proper signals because of seasonality factor.

Two important trends appear from the above data are:

  • In case of each month number of tourists have increased in every year
  • FTA in each month is highest in 2014

These two points simply corroborates the discussion we have previously that there is a slow and steady increase in FTA. To avoid the clutter, I have presented this trend 2012 onward in Figure 1 below. The graph shows clearly that recognizing the seasonality with the crest in Jan-Feb and the trough occurs in May, every year the number of tourists visiting India has increase every year. But does this portray the entire story? The answer is NO. It is too simplistic a conclusion to be made and could have been easily concluded that with economic revival, India’s inbound tourism has also seen an immediate impact.

Slide1

To prove this particular point, let us have a look at the Figure 2 and Figure 3. These two visuals exhibit growth rates in FTA to India and absolute change in growth rate in the same. If one carefully looks at these two visuals, a few points sharply indicate why the change in tourism behaviour did not start during end of 2010 when the world economy stated looking upwards.

Slide2 Slide3

  • In Figure 2, growth rates, year-on-year basis, in almost every month declined since 2009 to 2013. The representing growth rates during 2012-13 is the bottom most line and all other years follow a sequence in decline except February and April during 2011-12
  • While looking at this point one needs to remember that the base number has increased as the year increases; so it growth rates will always have an edge if it belongs to earlier years
  • In Figure 3, the absolute change in growth rates (Y-O-Y basis) are presented. This is similar to “first difference” that we normally consider in econometric modelling which plays crucial role in any trend analysis.
  • The graph shows that the absolute change in growth also behave almost in similar manner to that we identified in case of growth rates. The red line, which represents absolute change between 2012-13 and 2013-14, appears at the top.

This trend clearly suggests that though apparently it looked like that the inbound tourists arrivals to India has recovered the hit from global recession since 2010, the actual recovery has started only in 2014 January onward. Till then it was more of a falsified trend that might create a wrong perception regarding the recovery of the Indian tourism in terms of foreign tourists’ arrivals. This has significant implications for policy making as well as for core stakeholders in the industry. Also, while forecasting FTA, one needs to look into carefully at the variable behaviours. It is quite possible that lag effect might be much higher than generally though of.

Hotel Industry in India – Some Correlates between Prices and Macro Economic Issues

By Dripto Mukhopadhyay

Hospitality has become one of the major businesses in the India. Large number of international brands has entered the sector in recent times. The sector has been marked with increase in number of premium segment hotels in different parts of the country, along with smaller ones that cater the need for the middle class and lower middle class domestic tourists. In this particular blog, I would restrict myself in highlighting a few crucial attributes of the hospitality sector in India and some of the consequences thereof.

To start with let’s look at some of the macro economic indicators relating to hospitality sector. As obvious, hospitality sector includes hotels and restaurants. Though apparently this should include informal sector also, as the norm goes in national accounting system, data pertaining to this sector majorly reflects the trend of the registered sector because of sheer nature of the sector. Gross Domestic Product (GDP) relating to hotel & restaurant sector is presented in Figure 1. The visual presents the GDP of the sector at 2004-05 prices and the share of hotel and restaurant sector to total GDP of the country from 2000-01 to 2011-12. It is evident from the graph that hotel and restaurant sector GDP has increased to 3 times during the last decade starting 2000-01. It showed a gradual increasing barring the period 2008-09 and 2009-10 as the period was marked with global economic recession. However, the share of the sector in total country GDP rose till 2007-08 significantly and since 2008-09 suffering a dip followed by a stagnating share. This is a reflection of happenings in the world economy as well as of the Indian economy. Though apparently India recovered quickly enough from the recession, due to some of the fiscal measures by the Central Government, but the recovery was quite brittle in nature. It has become evident from high GDP growth registered soon after 2008-09, but poor GDP growth during last couple of years. Poor performance of industry sector, majorly due to reduced demand from domestic market, led the slow down.

However, investment in hotel and restaurant sector was not hampered by timid GDP growth during recent years. Gross Fixed Capital Formation (GFCF) in hotel and restaurant sector and its share in total GFCF of the country is given in Figure 2 below. There was a steady growth in investment in this sector, especially since 2003-04. The momentum dampened a little during the year 2008-09, but picked up again and has shown steep growth. The red line in the graph Continue reading

Price Index for Hotel Industry in India

By Dripto Mukhopadhyay

Whenever someone wants to work on estimating tourism demand or look into issues related price impact on tourism, price of accommodation is a crucial one to incorporate in analysis. In India lack of any time series on accommodation prices was a serious bottleneck for researchers who wanted to look into these relationships. Measuring price sensitivity is crucial for predicting tourism behaviour, be it domestic or international or for any specific country per say. This article tries to bridge that gap in a systematic manner through constructing a Hotel Price Index (HPI) for India. This HPI has taken care of different categories of accommodation also. In general, hospitality service providers are categorized into following by ministry of tourism as well as well accepted among the industry players:

  • Five star deluxe
  • Five star
  • Four star
  • Three star
  • Two star
  • One star
  • Heritage
  • Others

Heritage hotels have become popular during last decade or so. Whereas several other accommodation services are available currently, that cannot be categorized under anyone under star categories or heritage category such as service apartments, paying guest accommodations etc, which are clubbed under the category of others. An HPI at India level should represent all these categories and also should cover different corners of the country to be considered as a representative Index for hotel prices in India. The HPI presented in this article has used HVS data sets. Though HVS data is a robust one in terms of coverage, however, it captures information from 40 odd cities in India. Therefore, to some extent this HPI may be considered as slightly over-estimated one. The reason being hotels in remote areas, especially that are not well known tourist destinations, might have lower rates than that captured from the cities covered under the said survey. Continue reading

Arrivals of Foreign Tourists to India – An Overview

This is a presentation that discusses a few important issues related to inbound tourists to India. This is a part of a study related to forecasts of inbound tourists to India which I did during the beginning of the year 2010. To view the presentation, please click on the link below.

Arrival of foreign tourists to India

Forecasts of Inbound Tourism to India for 2009 and 2010 – A brief Analysis

By Dripto Mukhopadhyay

I am working on a paper related to inbound tourists to India. This paper will include identification of determinants and forecasts for inbound tourism to India at country and regional level. However, quite a few interesting facts have emerged related to Indian tourism during working on this paper. I want to share a small part of it including the forecast for total inbound tourism to India from all countries and regions of the world. I think this article might interest all my friends in the tourism sector in the world, especially in India.

Global economic recession has taken its toll on world tourism. India was also affected adversely and this was a real cause of concern for millions of those who are directly or indirectly linked to this potential sector. It affected the tourism sector hard, especially, from last quarter of 2008 till 3rd quarter of 2009. Presently, the situation looks like better compared to the months of core recession period. However, even if it is considered that the recession is over and we have entered into the recovery period, for most of the countries the recovery is expected to remain low during 2010 as well as for 2011.

Several incentives came into play from all sub-sectors of such as hotel industry, tourist operators, aviation industry etc. However, these incentives did not really play a major role since the period of recession was marked with large number of layoffs, salary cuts and their multiplier effect on the overall economies. This was combined with the incidents of 26/11 terrorist attack in Mumbai, which had shaken the entire country exposing the brutal faces of terrorism. The spread of swine flu must have also played its part on Indian tourism during this period.

In such a volatile situation, it is important that we are able to predict tourism activities, especially, for a short-term so that the players involved with the industry can plan their activities accordingly. I will limit my observations only to inbound tourism to India, i.e., foreign tourists’ arrivals (FTA) to India. Before coming into the forecast, I want to show the past trend in Indian tourism regarding FTA. We can see three distinct periods experienced by Indian tourism regarding this indicator. The figure given below shows these structural changes with vertical red broken lines.    

The data considered here for this analysis is from 1981 to 2008. The figure distinctly identifies the periods which are a) 1981 to 1985, b) 1886 to 2002 and c) 2003 to 2008. To substantiate the visual identification, I have presented the following table which shows average increase in FTA per year and average growth in FTA per year during these three periods.

Structural Change in FTAs Over Time

Period Average annual increase in FTA (%) Average annual growth in FTA (NO.)
1981-1985 0.20 -4957
1986-2002 4.01 62499
2003-2008 14.68 499273

 

For forecasting purpose I have used an econometric model. Since this is slightly technical in nature, I am not going into the complicated modeling part of the analysis, rather will highlight the dimensions that are important to understand for everyone. From planning purpose it’s important to understand the likely impact of any incidences like change in the economic growth pattern, change in petroleum prices, change in exchange rates, terrorism and several others. I have taken care of about 10 important indicators which include macro-economic as well as socio-demographic characteristics. Several models were run to identify the best possible model and the elasticity related to the explanatory variables.

The elasticity related to  a few important findings are:

  • Income (Gross Domestic Product as well as disposable income) is the most significant indicator making impact on tourism decision.
  • Exchange rate also plays an important role though not as strong as income.
  • Policy initiatives, especially on promotional aspects have a huge role to play in tourism demand. In case of India, “Incredible India Campaign” launched by the tourism department has a significant impact in attracting tourists to India. Thanks to the Tourism Ministry and especially to Dr. Amitabh Kant.
  • Economic liberalization has also played an important role, since opening up of the economy has generated lots of export import related activities which increases number of business tourists substantialy.  
  • Terrorist activities have an adverse impact; however, this is more short-lived than a long term one. The impact remains for a couple of month or so and also depends on originating country.

 

I have given here the forecast for 2009 and 2010. The forecast has considered the economic growth as predicted by International Monetary Fund (IMF). I have given three scenarios based on different economic condition of the world economy.

Estimated Total Foreign Tourist Arrival to India during 2009 and 1010

Year

 

Most likely scenario

 

optimistic scenario  

 

pessimistic scenario 
2009 5154714 5305754 5006500
2010 5532180 5854723 5224443