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
% Forecast points
||More than 90% accuracy
||Accuracy level 85% to 90%
|Low on accuracy
||Accuracy level less than 85%
Table 2: Regions and Country of Details of Forecasts and Deviation of Actual Foreign Tourists Arrivals to India
Tourism is one of the major compenent of foreign exchange earning for India. Since 2003, launch of Increible India campaign, India has seen a significant increase in number of foreign tourists visiting the country. Though it is still an insignificant share of total outbound torusim in the world, the scenario is encouraging over time. Even though the inbound tourism to India was hit substantially because of 2008 global recession, it recovering gradually with global economic recovery.
This particular blog has given a snpshot on how the inbound tourism has changed during last three and half years (till the latest data avaiable). the analysis provides a month-wise scnario so that seasonality involved in inbound tourism can be kept in mind while looking at the pattern.
The graph below exhibits the number of FTAs month-wise from 2010 january till 2014 June. Two important inferences can be made from this visual:
1. For this entire period FTAs have increased for every month.
2. It shows a seasonality in FTAs with peak during the winter, lean during the summer with marginal increase during the month of July.
The next visual exhibits the year-on-year monthly growth in FTA. The inference can be made from this graph is as follows: Continue reading
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
Posted in Destination development, economic instrument and tourism, Ecotourism, Factors of tourism demand, Sustainable Tourism, Tourism, Tourism and Climate change, Tourism Forecast, Tourism management, Tourism policy, Uncategorized
Tagged competition in hotel industry, green hospitality, Hospitality industry in India, hotel and restaurant GDP, investment inhospitality sector, Sustainable hospitality industry in india, Tourism in India, Tourism in India in 2012