Institutions and the Tourism Development in Pokhara
Dr.Om Sharma
Associate Professor (Economics), Department of Economics, PNC, TU, Pokhara
Abstract
This paper attempts to deal with the role and the impact of the various private institutions on the economic development process of pokhara city. The macro variables are introduced through the application of various economic models, such as, linear, longlinear and the multiple regressions. The empirical results have been estimated by applying annual data for the period of 1994 to 2004. The business tax income of the pokhara municipality and the total tourist arrival im pokhara are assumed as the development indices. The estimated regression equations exhibited a strong rolel and impact of the expenditure incurred for tourism promotion by pokhara chamber of commerce. However, number of hotels/restaurants /traval and trekking agencies demonstrated negative relation to the aforementioned dependents.
Introduction
Have a must see place in the world, Pokhara and its surroundings like Ghandruk, lost their glory days? Presently, to answer the sensitive questions as such is noto a difficult task. Whether there would be magnificent revival of the days of business boom as experienced earlier in the tourisam sector, sets forth a horizon of confusion to the stakeholders.Immortalized by ‘Happies’ in early 80’s the Freak street; and, ‘the Fewa lake’ where, Fishtail, the virgin mountain seemed to be crystal clear, have lost their glamour due to growing insurgency and the political instability in the Himalayan Kingdom. The major tourist’s hub of Nepal, Pokhara which may enormously decorate the friendly feelings, remains to be pilgrimage for all kinds of travelers. Mushrooming of the hotels that had intensified the competition and promoted cannibalization in the hotel industry has been forgotten due to the absence of peace and security in the country. Even if the numbers and quality of (tourism) jobs are debatable, the now, tourism undoubtedly has becom ‘a kind of religion’ (observation, 1998) and ‘Part Of life style’ (Bhatiya: 1996).
Men are powerless to secure the future; institutions alone fix the destiny of nations (Napoleon: 1815). Accordingly, institutional factors also play a role of caralyst as tourism development is concerned.It has been observed that a substantial transformation in tourism related institutions, has led tourism development in Nepal during the last few decades. In this regard, investment made by various mational as well as international institutions on accommodation, transportation, communication, and other necessary services; is supposed to trigger tourism earning and employment along with economic and social transformation. Being highly intersectoral in nature, tourism not only involves a a multitude of public sector components at national, regional and local levels of government, but also various segments of the private sector ( HMG : 1983, 75 )
Finding the role of the private institutions as one of the objectives, this paper makes an empirical inquiry of the private sector institutions in raising the inflow of tourist and the income of the pokhara city. The role of the private sector may equally be effective to promote tourism, which enjoys a rather privileged status, and strongly backed by the government incentives and support (Sharma: 2001).A vision for the future can not exist in a vacuum; it must be solidly grounded in reality. There is a clear recognition that institutiomal framework for tourism development needs a further change. To this end, a wellknown fact that cannot be denied, is the efficient role of private sector as compared to the public sector.
The unavailability of the investment data has limited this part of the study to concentrate within the periphery of the expenditure made by Pokhara Chamber of Commerce & Industry and the growth of the institutions like hotels, restaurants and travel/trekking agencies. To treat things in a sensible and realistic way, some other lagged variables have also been considered.
Data and Methodology
In this study, time series data have been employed. The data on total tourist arrival in pokhara (TTAP) and the number of hotels, restaurants, travel and trekking agencies (NHTTR) were obtained from the Tourist Information Office. The data regarding the expenditure on tourism development and promotion by Pokhara Chamber of Commerce & Industry as well as the municipality business income (MBI) have been collected from the respective institutions during the first week of the month of August 2014.
Before empirical tests are carried out, it is pertinent to state about the data problems associated with the estimation of the impact of the money expenditure of the institutions like PCC on the economic development process of Pokhara municipality. The data regarding the tourist arrivals is available since 1976 whereas for MBI and CME pcc data are avaailabae from the year 1986 and 1994 respectively.
In this study, along with the trend functions ordinary least squares (OLS) method has been applied to the simple linear, log linear and the first difference form under the single equations system. Thus, the various models under the single equations system are examined and the results of the empirical works are discussed.
The simple model as applied is in the linear form. The model may be presented in the following simplified version as
TTApt = a_{₁}+a_{₂} CME_{pcc}……………………………………………………………………………1.1
Where, a_{₂}>0
MBIt = a_{₁}+a_{₂} CME_{pcc}……………………………………………………………………………1.2
Where, a₂>0
Moreover for seeking remedial, as there is presence of serial correlation in the equations 1 and 2, the known situation of the structure of auto correlation where P < 1 and €_{t }follows the OLS assumptions of zero expected value, constant variance and non autcorrelation, let the equation be reverted as :
TTA_{pt} = βo + β₁ CME pcc_{t} + U_{t }……………………………………………………………………….. 1.3
In this connection, if equation 1.2 holds true at time t, it also holds true at timeI
Hence,
TTAp _{t1 }= β + β1 CMEpcc _{t1 }+ U _{t1 }…………………………………………………………………….1.4
Multiplying the equation 1.3 by p on both sides, we obtain
pTTAPp_{t1 }= pβ0 + pβ_{1 }CMEpcc_{t1 }+ pU _{t1 }………………………………………………………… 1.5
Subtracting the equation 1.4 from 1.2 gives
(TTAp_{t} – pTTAp_{t1} ) = βo (1p) + β_{1 }CMEpcc_{t} – pβ_{1} CMEpcc_{t1} + (U – pU_{t1})
= β (1p) + β_{1 }(CMEpcc_{t} – pCMEpcc_{t1} ) + €t ………………………..1.6
TTAp* = β + β_{1} CME* + €t……………………………………………………………… 1.7
Β_{1}>0
In the above equation (1.6), since €t satisfies all the OLS assumptions, one may proceed to apply OLS and Obtain estimators with all the properties namely, minimum variance. Thus, a regression that is known as the generalized difference equation has been used. By applying theil technique to obtain an estimate of p (Coffecient of autocorrelation) as:
Where, N=total number of observations, d=DurbinWatson statistic, and K= number of coefficients (including the intercept).
Using the estimate p, data are transformed as in the equation 1.6. The Intercept term in fact is an estimate of βo (Ip). Thus, an estimate of βo can be obtained as βo = βo/ (I – p).
The twovariable model studied extensively is seldom so simple for economic theory.A number of other variables are also likely to effect total tourist arrival and the income of the pokhara municipality from business tax.Besides money expenditure as performed by PCC, the number of hotels /restaurants/travel and the trekking agencies, the lag values of MBI and the time may be accounted for some crucial variables in this regard. In most multiple regression analysis involving times series data it is a common practice to introduce the time in addition ti several other explanatory variables (Gujrati, 1978). Therefore, the single equation model needs to be extended to cover models involving more than two variables (Sharma: 2001, 177190). The multiplevariable population regression function (PRF) may be expressed as:
Y_{1 }= β_{1 = }β_{2}X_{2}+ β_{3}X_{3}i+ β_{4}X_{4}i+ β_{5}X_{5}i+U_{1}
_{ }Β_{2}>0, β_{3}>0, β_{4}>0, β_{5 }>0,
Where, Y refers TTAp and MBI the dependent variables, X2, X3, X4 and X_{5} refer the explanatory variables which refer expenditure for tourism promotion by PCC, the lag income of Pokhara municipality through business tax, the number of hotels/restaurants, travel and trekking agencies, and time respectively.
Pattern of Growth of the expenditure for Tourism Promotion
The money expenditure as incurred by Pokhara Chamber of Commerce & Industry during the period 1968 to 2004 for the promotion of tourism might have produced positive effects on the economic development process of Pokhara Submetropolitan city. Organizing and conducting various programs related ta tourism promotion, permits one to categorize under the following heads such as, a) training to tourism promotion, b ) conventions, seminars/exhibition, c) trade fare and constructive works, d) Publications, and e) social contribution.
The expenditures are summed up as under.
Table 1.1
Expenditure for Tourism Promotion
Year 
TFIP 
CES 
TFCW 
PUBS 
SC 
TES 
1968 
14000.0(100.0) 
14000.0 

1994 
98764.0(80.2) 
00.00 
20586.0(2.1) 
3834.0(3.1) 
123184.0 

1995 
181829.0(56.4) 
83815.0(25.80) 
32442.5(10.1) 
00.00 
25000.0(7.7) 
322396.5 
1996 
292574.5(51.9) 
271556.0(48.1) 
00.00 
00.00 
564130.5 

1997 
346719.5(62.0) 
166330.5(29.7) 
6000.0(1.1) 
00.00 
40389.5(7.2) 
554130.5 
1998 
104020.5(18.6) 
84215.5(27.9) 
00.00 
64052.0(21.2) 
50000.5(16.5) 
559439.5 
1990 
00.00 
6778.0(11.0) 
00.00 
00.00 
55000.0(89.0) 
302288.0 
2000 
33851.0(8.9) 
00.00 
7224.0(1.9) 
318646.0(83.9) 
20000.0(5.2) 
61778.0 
2001 
00.00 
00.00 
00.00 
00.00 
15000.0(100.0) 
15000.0 
2002 
30841.0(23.8) 
00.00 
00.00 
00.00 
98481.0(76.2) 
129322.7 
2003 
00.00 
00.00 
00.00 
00.00 
20000.0(100.0) 
20000.0 
2004 
8209.0(3.4) 
226083.0(95.2) 
00.00 
00.00 
3500.0(1.5) 
237792.0 
TES 
1096809.2(40.2) 
838088.0(30.7) 
80252.5(2.9) 
386532.0(14.2) 
327370.5(12.0) 
2729052.0 
Source: Pokhara Chamber of Commerec & Industry, 2004
( ) Parentheses Indicate Percentage
To give a bird’s eye view regarding the trend of the expenditurs made on the promotion of tourism in pokhara and its surrounding, it is highly pertinent to apply the curve fit. The cumulative sum of the money expenditure as incurred during the period of 1994 to 2004 for tourism promotional activities exhibits the following results :
Table 1.2
Models of Curve Fit
S.N. 
Models 
Dependent Variable 
Constant 
Coefficients 
R^{2} 
F.Value 
D.F 

1.1 
Straightine 
CSE_{pcc} 
64673.13 
+258805.21(T) 

23879.92 

(10.84)*** 
0.92 
117.46 
10 

1.2 
Quadratic 
CSE_{pcc} 
710443.47 
+535563.92(T) 
21289.13(T)^{2} 

55909.7 
4186.69 

_{ } 
(9.58)*** 
(5.08)*** 
0.98, 
217.64 
9 

1.3 
Compound 
CSE_{pcc} 
94340.23 
(1.4245)^{T} 

0.119 

(11.97)*** 
0.64 
17.94 
10 
*** Significant at 1 percent level of significiance
(The data in parentheses refer t – value)
From the standpoint of policy formulation, it is appropriate to note the background that intensifies the prospects of tourism development in pokhara. The observation of the results as presented in the above table 1.2 helps to deduce the fact that the seconddegree parabolic curve is a good fit to the data covering the period 19942004. The most serious limitation of the method is the determination of the type of the trend curve (Gupta & V.K. Kapoor: 1994, 123). Keeping this constraint in view, apart from R^{2}, Fvalues, and t values, the very model was selected that showed comparatively less standard of the estimates (ESS). Besides, the trend values for the period 2005 to 2010 are found to be in increasing order. The trend values are stated as under:
Table 1.3
Year Trend Values 
2005 3299795 
2006 3558600 
2007 3817405 
2008 4076210 
2009 4335015 
2010 4593821 
Trend of Tourist Arrival in pokhara
A glance at the tourist arrival in Pokhara is of paramount importance. Until the mid20^{th} century, Nepal remained a closed country due to intractable barrier and adverse government policy. When the government policy changed from suspicion of foreigners to one of reception, tourists are explorers and climbers started to increase subsequently (Gurung 1989:148). Indian influx are Gujirati and Marathi urban tourists visiting Pokhara during the summer offseason (Dixit: 1996).Except for some years the travelers sprouted up at a very sound rate even in Pokhara.The compound growth rate of the tourist arrival (5.13%) in Pokhara seems to be moderate for the period 1976 to 2003 that is visualized by the equation 1.5 stated as below. However, over the previous years tourist arrival in pokhara has been showing a vertically declining trend i.e., bye 22.38 percent in 2001 and by 27.4 percent in 2002, respectively. For the past few years the flow of both western and Indian tourist to Nepal has declined for reasons internal as well as external (Nepal: 2003). Dixit (1996, 459) blames on the following factors for declining trend. The most detrimental factors are : two air crashes in quick succession of thai International and PIA; unprecedented floods and landslides; political turmoil and ‘Nepal Bandhas’,pollution in Kathmandu and on trekking trails; hikes in visa fees, and the Ayodha related turmoil in the Indian market.
TTAp_{p }= 18519.119 (t) R^{2 }F d.f ………………………… 1.4
254.629 0.81 112.36 26
TTA_{p} – 25492.288 (1.05126)^{ t }0.87 175.23 26 …………………………… 1.5
0.00397
264.814***
Growth Pattern of Hotels
Hotels form an important and vital segment of the tourism infrastructure. The economic impact of hotel industry particularly in export earning, employment generation and income distribution is widely appreciated in tourism literature (Panda: 2000). Moreover, hotel is an industry with great spatial fixity, an exceptional degree of decentralization, and an immense volatility of taste (Urry, 1990:4165). The provision of hotels and other supplementary accommodation facilities are regarded as the keynote to promote tourism industry (Mahajan and ET. Al., 1999:120).
Pokhara, a worldclass attraction is rather a remarkable aspect to observe an increase in the hotel occupancy rate by 1.3 percent (Sharma: 2003, 3854). Viewed with reference to regional basis, Sharma estimated that the western Development Region (WDR) could generate the highest, 56 percent, support staff employment in trekking during the year 1998 (Sharma:2003, 2834). Thus, the trend of hotels in Pokhara is also to be analyzed to click the picture of tourism growth pattern.
The time series data regarding the number of hotels/trekking/travel agencies and the restaurants are considered for the full period of 1990 to 2003. The total number of hotels, travel and trekking agencies and restaurants are added and the composite from of the variable NHTTAR is derived for stastistical purpose. In this regard, the linear and the compound functions are applied so as for defining the growth trend of the institutions those are directly related to tourism development in Pokhara. The results of the above functions as given as under :
NHTTR^{2} = 501.486 + 34.086 (t) R^{2 }F d.f …………………….. 1.6
1.604 0.97 451.469 12
21.248***
NHTTR = 4.276343 (1.191309)^{t} 0.969 381.496 12 ………………………….. 1.7
0.010677
11.577***
The results exhibit that number of hotels, restaurants, travel and agencies has increased in Pokhara by 19.13 perecent per annum during the period 1990 to 2003. It is, however, opined that a comparative study of the growth in the number of tourist, number of hotels, travel and trekking agencies does not really illustrate the reasons for growth of tourism (NRB: 1989).Investment loan at lower interest rate and the adoption of the tax exemption policy have been cited as the responsible endogenous factors that led to the growth in the number of hotels and other related tourism institutions (Sharma: 2001, 54). Tourism and the hospitality industries are generally now a vitally important part of the London ecomomy. It is responsible for at least 5 perecent of the capital’s GDP and up to 10 percent of its jobs (Bull and Church: 1996).
Log Linear Models
Having discussed the trend of tourism institutions, tourist arrival, annual income of the Pokhara city, and the tourism promotional expenditure incurred by PCCI, it is equally important to delineate the factors as responsible for improving the economic condition of Pokhara. Consequently, the whole aspect has been submitted to xray scrutiny to arrive at the truth. Accordingly, tourist arrival to Pokhara (TTAp) and annual tax income of the city are assumed as the dependent variables. The money expenditure incurred by PCCI for tourism promotion and the number of the hotels/restaurants/travel and trekking agencies are hypothesized as the independents. These factors indeep play some critical role in raising the economic benefits to the area as concerned locally.
The basic starting point is the examination of a direct relationship between the development indices and the amount of the money spent for tourism development of the Pokhara city by the Chamber of Commerce (CSEpcc). Keeping the above empirical finding at hand, it has been necessary to examine some of the commonly used regression models, which are linear in the parameters but are not necessarily linear in the variables. Accordingly, a cursory effort has been made to check the average elasticity of the cumulative money expenditure made by Pokhara Chamber of Commorce & Industry to the various development indices with the presumption as noticed earlier for tourism promotional activities. The results of all the subsequent regressions, all of which are measured in loglinear are given below:
In TTAp = 9.331+0.141 in CME_{pcc }………………………………………………………….. 1.8
0.057
2.493***
R^{2 }– 0.437
F – 6.213
SEE = 0.1605
With reference to the above result, it may be argued that an increase in the money expenditure of the institutions (PCCI) for tourism development has a positive effect on the development indices like total tourist arrival in Pokhara. An increase of 100 percent in the cumulative money expenditure of PCCI (CMEpcc) leads to an increase in total tourist arrival in Pokhara (TTAp) by 14.1 Percent. The results maintain significance at 5 percent, and the fit quite good. It is from the above results that the degree of association between the variables is quite less. Thus expecting serial correlation between the variables, it is practicable to apply theil (1961 : 79306) corrective measure in the first order difference form vhere p^ is known through the formula ^p = (Id/20). Modifying the regression in that manner reveals the results as following:
In TTAp = 3.236+0.356 in CMEpcc …………………………………………….. 1.9
0.145
2.451**
R^{2 }– 0.40
F 6.008
SEE = 0.956
The application of the regression in first difference, order illustrates the results that of similar to the previous model. Although, all the necessary statistics have revealed the good fit of the model except R^{2,} that explains only 40 percent of the variation.
Multiple Regressions
Despite the good fit of the models, the low explained percent of variation with regard to total tourist arrivals in Pokhara has driven to move ahead to test the multiple linear regression. The results derived in accordance with the above presumption are expressed as under.
TTAp = 92468.382 – 313.792 (NHTTAR) +5.030E02 CSEpcc …………………………… 1.9
80.306 0.011
3.907*** 4.519***
R^{2} – 0.76
F – 10.906
SEE = 9090.5358
The introduction of the compositve variable NHTTAR into the model however, shows with the negative sign and magnitude significant at 1 percent level of significance. Moreover, introducing the time as an independent variable has also been performed in multiple regression analysis. The application of the backward method has removed time. It is desirable because time itself seems to be an insignificant factor with negative sign and magnitude. Accordingly, the results of the model are summed as under:
TTAp = 1951280 + 5.049E02 CMEpcc – 291.341 (NHTTAR) – 993.584 T …………1.10
0.012 273.77 10798.96
4.133*** 1.064 0.086
R^{2 }– 0.757
F – 6.242
SEE = 9812.79
The results of the above multiple regression model (1.10) exhibit vividly that the variables like NHTTR as well as time are the insignificant factors although negative sign and magnitude of the variables are being observed. Thus, after indicating some sort of association between tourist arrival and the promotional expenditure as incurred by the Pokhara Chamber of Commoerce, it is felt necessary to move on to the function, which considers the models of log linear one.
In MBI = 21.056 + 1.697 in CMEpcc – 5.022 In NHTTR ………………………………. 1.11
0.808 1.685
2.101* 2.98**
R^{2 }0.70
F – 5.749
SEE = 0.9033
In TTAp = 8.988 + 0.396 In CMEpcc – .580 In NHTTAR ……………………………………. 1.12
0.112 0.234
3.359*** 2.481**
R^{2 }– 0.70
F – 8.185
SEE = 0.1252
The results obtained from the above equations 1.11 and 1.12 confirm a priori notion in terms of both sign and magnitude. The coefficient of the expenditure of Pokhara Chamber of Commerce & Industry (PCCI) on tourism development programe play a dominant role of the factor number of hotels, restaurants, travel and trekking agencies is concerned; both the equations 1.11 and 1.12 have expressed the significant coefficient in negative sign. For this, backward criterion method has been followed and the SPSS program excluded other variables from the model. The excluded variables are the lag values of MBI, and TTAp, and the time. The supply of the hotels, restaurants, travel and trekking agencies seems to be significant but at negative sign and magnitude. It is in fact the cause of the declining trend of both the dependents MBI and TTAp. The most detrimental factors to make the tendency of declination may be accounted for the Maoist insurgency, unstable governments, and the absence of peace and security within the country.
Empirical findings
The major findings from the empirical analysis for the role of various provate sector tourism promotional institutions are summarized as follows:
 The empirical analysis of the data, with loglinear models of the first order difference, well justifies that the expenditure incurred by PCCI for tourism promotion contributes to raise tourist arrival as well as the business tax income of the municipality.
 The application of the multiple regression analysis too confirms the positive and the significant role of PCCI in raising the tourist and the business tax income of the Pokhara municipality.
 The declining trend in tourist flow has made the number of the hotels, travel and trekking agencies as significant with negative sign and magnitude.
Conclusion
Although a nonprofit making institution organized by the profit making personnel in the private sector, Pokhara Chamber of Commerce & Industry (PCCI) has been playhing a conducive role for the development of tourism in and around the pokhara city. This implies that to capitalize the world class potential of Pokhara, strong commitment on the part of the government and an enthusiastic involvement on the part of the private sectors are going to be required.
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