Paul Robson
email: p.j.a.robson@durham.ac.uk

Robert Bennett

Paying fees for government business advice: an assessment of Business Link experience

Keywords: Consultancy, Fees, Business Link, Customer satisfaction, SMEs Consultancy, Fees, Business Link, Customer satisfaction, SMEs

Business Link in Britain provides a unique opportunity to examine a government policy support to small firms which has targeted fee income as a major part of its management objectives in order to increase the 'sense of value' of the services offered. The paper examines the influence of fees on client impact and satisfaction.

It finds that fees have no significant relationship with client satisfaction or impact.

Government targets and manager/advisor policies have, therefore, been wrong to pursue an explicit fee-based targeting strategy. Instead, satisfaction and impact are most significantly influenced by the character of the Business Link provider, being significantly higher for franchises managed by chambers of commerce and other agents, and being poorer for independent stand-alone providers. Service type has a significant influence on the propensity to charge a fee and on service impact. SME characteristics have little influence on client evaluations. The policy implication is that advisors should focus on what they do best and can quality-assure; in other cases they should use referral to other professional advisors. The scope to raise fees from government advice services is, therefore, opportunistic and limited, and should not be incentivised

Paying fees for government business advice: an assessment of Business Link experience

Introduction

Advice and counselling services provided to Small and Medium-sized Enterprises (SMEs) by government agencies, or by public-private agencies that receive a level of government support, are a widespread phenomenon in the US and in Europe (see e.g. [START_REF] Chrisman | The Small Business Development Centre programme in the USA: a statistical analysis of its impact on economic development[END_REF]MetaMetrics Inc, 1986;OECD, 1995OECD, , 2000;;EU SMEs Observatory, 1993[START_REF] Grayson | Business Links no myth[END_REF]. The US Small Business Administration, established in 1953, for example, provides financial, technical and management assistance for business start-ups, and growth. Similar initiatives have now been adopted throughout Europe, in part reflecting the value now placed on SMEs in the development of economic growth.

Despite this widespread development, the role of any fees that are charged in the delivery of services is a neglected topic. Fees are rarely mentioned in promotional literature, and policy evaluations have almost entirely neglected the issue of whether a fee was charged for the service and what impact this had on the managers, advisors or clients. Yet the scope to charge SMEs a fee may have a major influence on how advisors perform and is likely to be a strong influence on SME evaluations of advisor performance.

The British government's advisory system for SMEs has, however, made fees a major part of its targets and means of operation. First established in 1993, the Business Link programme has developed a network of local advisory centres which deliver information, advice and counselling services across a wide field of different SME activities -ranging from financial and accounting advice to exporting, training, and product and process innovation. A key target for this system was originally to be selffinancing. By 1997 this became a target to be part self-financing through fees. This was sought, in part, in order to reduce the costs to government, but also because politicians and policy designers felt that SMEs would more highly value a service that they paid for (or at least to which they contributed). The emphasis on fee targets was down-played in government aims after a redesign of the system in 2000, but, as we show below, fees have remained an important part of Business Link finance.

This paper assesses what lessons from the use of fees are offered to government advice schemes in other countries by the special experience of Business Link. Whilst in theory a market opportunity may exist for government services of this kind, it remains an empirical question how fees affect the effectiveness of these services.

Previous assessments of the use of fees have shown that they have little or no relation with client evaluations, or may even be negative (Bennett andRobson, 2000, 2005).

However, that analysis was based on a smaller scale sample and did not fully control for the influence of service type and other factors in influencing fee charging capacity.

The current paper develops a fuller analysis using Instrumental Variables and a wider range of controls to measure Business Link management characteristics.

The arguments that led Business Link to emphasise the use of fees are discussed in the next section. The main part of the paper then assesses the effect of fees on SME client assessments. New evidence from a large-scale survey of SMEs is used to compare assisted businesses that were, or were not, charged a fee.

Fees and Business Link

Business link was developed by the British government as a new, locally-based SME information and advice service to replace previously centralised schemes. The theoretical and political justification for the decentralisation of business support to local partners focused, as specified in the original DTI (1992a) Prospectus, on a belief that there was deficient business demand, the market was failing to provide sufficient advice, and that government-sourced services could increase the resources available to firms and hence improve the overall rate of business growth, and thus economic growth of the economy as a whole. The local aspect was seen as the best way to engage with SMEs by tailoring and marketing services in specific locations.

Improvements in tailoring services were also seen to need the involvement of the private sector in provision and an improved customer focus and professionalism (DTI, 1992b). One means by which this was sought was to charge fees to clients. There were two aspects to the aim of charging fees. The first was to re-align the partners who collaborated in the supply of services. The re-alignment of partner services was sought because if each partner continued to receive the same subsidy from government that it had previously received then government believed that little real change would occur in the services delivered. In the words of the senior minister at the time, Secretary of State Michael Heseltine (1992, p.9), "There is already….plenty I would have thought to lever a major uplift in the quality of current support activity". Indeed, Heseltine initially argued that the long-term objective of the initiative should be that it should be entirely self-financing, with government support seen as essentially pump-priming. The Prospectus for Business Link, therefore, sought that Business Link "should move to self-sufficiency as rapidly as possible" (DTI, 1992a, p.3). As a result, in the early phase of Business Link the local partners had to build into their financial and business plans a means to achieve a selffinancing target which was initially set for the end of a five-year pump-priming period.

By 1997, the fully self-financing target was reduced to one which set 25% as the target for fee income. The Chair of the government's panel to assess Business Link local operators, David Grayson, came to the view that "Business Links are not expected to survive on their own without public funding" [START_REF] Grayson | Business Links no myth[END_REF]. The more cautious approach was reflected in [START_REF] Grayson | Building a network for business co-operation[END_REF] statement that the government should be "funding services where there is market failure" and "should be charging for some of their services" rather than all, with "the percentage of the total budget that is generated from client fees" used as a benchmark rather than a target for specific individual services; i.e. fees should be charged only where opportunities arose. This confirmed the views of private sector advisors. For example, Barclays Bank (1996, p.96) stated that "it is not viable to assume Business Links should be entirely selffinancing. A continuing element of government support will, therefore, be required".

The 25% target figure was set as "a rule of thumb. It is not scientifically based, but is considered to strike a reasonable balance between the need for Business Link to be a commercial body and the need to address market failure" (DTI, 1999b).

The second reason why fees were sought was to improve client valuation: it was thought that clients would better value what they paid for. The government believed 6 that the more that Business Link tried to emulate the private sector, the higher service quality would become (FSG, 1997;quoted in Priest, 1999). [START_REF] Grayson | Business Links no myth[END_REF][START_REF] Grayson | Building a network for business co-operation[END_REF] and DTI (1997a) believed that customers better valued what they paid for. This became a key part of the Service Guide to which local partners worked (DTI, 1997a). Grayson stated (1996, p.133): "charging is about credibility, demonstrating value and setting the right culture. ….small companies value much more those services for which they are paying …. They must be run in a business-like way and operate commercially (albeit with a clear public purpose)". The 2000 re-design of the system continued this view. For example, DTI (1999a, p.20) acknowledged that "charging for value-added service remains an important principle ….Franchisees will, therefore, be expected to have an effective charging policy ….(which can) assume that the existing approach to income generation, including the current broad assumption of 25% of income from customers, will continue".

David Irwin, the first chief executive of the Small Business Service, which was the awarding body for Business Link contracts in 2000, confirmed that the service "won't be free. I do believe that people in business should be paying something for good quality advice" (quoted in Financial Times, 4 May, 2000). Indeed, this is restated formally in the Business Link Strategy 2001/04: "for more intensive support, including making use of business advisors, it is reasonable to expect customers to make a contribution towards the cost of the service. It will be appropriate for that contribution to increase as the relationship develops" (SBS, 2001, p.14). However, the specific target of 25% fee income was dropped after 2001, and the government "will not use income generation as a performance measure". Despite this "Business Link will be expected…to develop their own pricing arrangements" (SBS, 2001, p.14). Hence, although fees have now been down-played, they remain part of the Business Link process, and the succeeding chief executive of the Small Business Service, Martin Wyn Griffith, retained a concern that businesses value the service they receive, and that they may better value what they pay for. For example, he has quoted figures for the payback rate of benefits to SMEs as a return for the costs of their paying for advice, using this as a model to justify government support for SMEs [START_REF] Griffith | Delivering effective growth and support for small firms, Speech to QMW Public Policy Seminar[END_REF]. Despite the claims for the benefit of fees, a significant body of criticism has suggested that fees can distort the behaviour of Business Link managers and their advisor staff and undermine the client experience. The recent strategy for Business Link acknowledges that "charging…has been a contentious issue, as it can distort priorities" (SBS, 2001, p.14), and that "it should not dictate priorities to distort actions" (DTI, 1999a, p.19). But the model of intensive advice, coupled with fees, inevitably does produce distortions as a result of the tension between objectives: whether Business Link is truly gap-filling or just trying to raise income; whether it fills a market failure or is competing with the market using government subsidies; whether the services being actively marketed with the bait of subsidies will actually do the SME any good; and whether the emphasis on fees encourages the retention of clients, thus undermining the role of Business Link and its PBAs as a neutral broker, reducing the likelihood of referral of clients to the most appropriate external supplier [START_REF] Sear | Business Links and Personal Business Advisers: selling services irrespective of client's needs[END_REF][START_REF] Hoc | Trade and Industry Committee, 5 th Report[END_REF][START_REF] Laforet | Assessing consultant quality for SMEs -the role of Business Links[END_REF][START_REF] Lean | An examination of the developing role of personal business advisors within Business Link[END_REF]Mole 2002a, b;Bennett andRobson, 2000, 2003). A survey by [START_REF] Mori | Business Links -wave 5[END_REF] for DTI showed very ambiguous evidence of client support for Business Link fees: 38% of respondents felt that the services were worth paying for, 19% did not, and 43% did not know. Similarly 37% felt Business Link represented good value for money, 11% did not, and 57% did not know. Indeed, the chair of the Small Business Council, set up to advise government on SME policy, acknowledges that "there is a structural flaw in that the support they (Business Link) offer is partly financed by the services they sell" (William Sargent, 2002, p.31) The more general literature on how SMEs use and value business advice and consultancy does give some support to the idea that the costs of advice positively influence client assessments. But it is an adventurous conclusion to suggest that this literature offers strong guidance to how a governmental service should be organised, or that costs alone rather than service intensity and quality are the main positive influence on client experience. For example, [START_REF] Bennett | The advisor -SME client relationship: impact, satisfaction and commitment[END_REF] compared various suppliers of advice to SMEs and find client satisfaction and fee level (total cost) negatively related in general, and this is particularly true for the use of private sector advisory sources. For public sector sources there is no significant relation of fee level and satisfaction. This is evidence from a relatively small sample of SMEs and hence cannot control for differences in service types or different modes of 8 Business Link service delivery, which are both likely to be influential in the form of relationships evident. However, it suggests serious doubt that the use of fees per se offers any guaranteed route to improved client evaluation. Instead satisfaction and client impact appear to be chiefly related to service intensity.

The service experience (quality, field and intensity), then, as much as the mode of delivery or fee may be the key influence on satisfaction. Even when fee targets were at their strongest, there was no uniform charging policy; it varied between Business Link operators in different areas, and varied within each operator by service field and advisor propensity to charge (see e.g., [START_REF] Sear | Business Links and Personal Business Advisers: selling services irrespective of client's needs[END_REF][START_REF] Laforet | Assessing consultant quality for SMEs -the role of Business Links[END_REF][START_REF] Priest | Business Link services to small and medium-sized enterprises: targeting, innovating and charging[END_REF][START_REF] Lean | An examination of the developing role of personal business advisors within Business Link[END_REF]. As a result, most assessments of Business Link services show strong variance in the type of services normally carried a fee. [START_REF] Priest | Business Link services to small and medium-sized enterprises: targeting, innovating and charging[END_REF], for example, found that Business Link fees were charged for diagnostic services in 80% of cases, for PBAs is 67% of cases and for financial packages and innovation and technology advice in 55% of cases. Other services experienced fees in a range from 6% to 47% of cases. There is thus a great range of fee behaviour within and between Business Link operators depending on service types, and this tends to be directly related to the service intensity (consultant hours or days required) of each client experience.

Similar results are evident in DTI (1997b) financial statistics and in preliminary assessments by [START_REF] Bennett | The Small Business Service: Business support, use, fees and satisfaction[END_REF]. DTI monitoring statistics for 1999 show a level of about £32m per year in fees being raised from about 100,000 clients, with a mean fee level of £300 per client. This is about 25% of the clients using the service, and they contribute about 9% of total income. This is the same level as in 1997 [START_REF] Priest | Business Link services to small and medium-sized enterprises: targeting, innovating and charging[END_REF]. The figure seems to be broadly stable, since 2002 and more recent data show fees still to be 8.5% of total income, but the proportion of SME users experiencing a fee has risen to 38% [START_REF] Bennett | External advice and Business Link, Chapter 5[END_REF]; hence, there are a greater number of firms experiencing fees, but their average costs are now lower.

Hence, although fees are certainly charged, the previous evidence for the positive influence of fees on client assessments is meagre. What evidence there is suggests that the scope for fees to be charged varies considerably by service type. Given the continued strong use of fees by Business Link in order to bridge their income gap, and Cosh and Hughes (2003). In summary, the CBR survey is a mail-out with telephone follow-up drawn from the sampling frame of Dun and Bradstreet, with random selection from stratified quota samples for manufacturing and business service firms over the SME size range of 1-499 employees. Tests of nonresponse bias show the sample to be unbiased and representative with respect to firm size, sector and age. The respondent sample size is 2127 of which 24% are users of Business Link. This is a large-scale survey, which offers a means to assess government business support on a comparable basis across different services fields.

The second survey is of the Business Link operators themselves. This was undertaken by mail with telephone follow-up to cover the same 2002 year as the SME survey and covers the early stage of the period in which fees were de-emphasised. It has a 100% response rate. Some additional financial details for each Business Link are added using the legal register of companies where Business Link accounts have to be registered (Companies House records).

These surveys provide information on SME clients and the local Business Links. In the rest of this paper we first assess how SMEs use Business Link and then assess how fees influence SME evaluations of impact and satisfaction. This is followed by assessment of how fee charging strategies differ between services and local franchise operators, after controlling for other differences in SME client characteristics.

Client evaluation

Previous analysis of Business Link has shown that it has made considerable impact on the market for business advice. Even in its early years, awareness of BL quickly reached 70% within 1-2 years of local outlets opening [START_REF] Mori | Business Links -wave 5[END_REF]. Use of BL by the end of 1997 had reached 9% of all firms with at least one employee and 19% in the main target group of firms with 10-199 employees (DTI, 1997b, Monitoring Statistics). Government impact studies have suggested very positive impacts of BL advice on turnover and profits [START_REF] Ph Group | Assessing the impact of Business Link operators on significantly assisted business-Cohort 1[END_REF]. Satisfaction assessments, whilst low in early stages (see e.g. DTI Monitoring Statistics; [START_REF] Priest | Stimulating the performance of SMEs through Business Link: An assessment of customer satisfaction, dissatisfaction and complaining behaviour[END_REF], have increased.

By 1997 BL had become the single most used government source of advice, with a fairly high emphasis on intensive support involving site visits and/or contract relationships with clients [START_REF] Bennett | The use of external advice by SMEs in Britain[END_REF]2000;[START_REF] Bennett | The selection and control of management consultants by small business clients[END_REF]. Subsequent development has seen the use of Business Link services exhibit steady growth in market penetration, increasing from 21% of established SMEs (with one or more employee) in 1997 to 24% in 2002 [START_REF] Bennett | External advice and Business Link, Chapter 5[END_REF].

The assessment below uses two measures of client evaluation: impact and satisfaction.

The impact of business advice on SMEs is a complex phenomenon inviting both 'hard' and 'soft' outcomes (such as increased profits or sales, as well as improved ability to manage, solve problems or to learn) [START_REF] Hill | Differences in the consumer decisions process for professional vs. generic services[END_REF][START_REF] Nowak | Antecedants to client satisfaction in business services[END_REF]. The survey did not allow scope for all the different dimensions of outcome to be assessed. Instead a single measure of impact in five categories is used.

The respondent is asked to evaluate whether the advice was crucial (5), important (4), moderate (3), little (2), or had no impact (1) to the firm meeting in its business objectives. The mean score for Business Link is 2.4 which is between little and moderate.

Satisfaction is used as a second assessment criterion. In our survey the respondent is asked to rate the advice received in four categories: very satisfied, satisfied, dissatisfied and very dissatisfied. The overall satisfaction level (% either satisfied or very satisfied) is 81.5% in 2002 [START_REF] Bennett | External advice and Business Link, Chapter 5[END_REF]. Satisfaction is an important complement to impact as a measure of client outcomes. It is more intuitive and based on feelings and perception, often deriving from the process of personal [START_REF] Nowak | Antecedants to client satisfaction in business services[END_REF]. Satisfaction will reflect criteria such as level of personal attention, confidence they feel in the adviser, speed and efficiency in dealing with queries, and other predominantly 'soft' elements of service delivery [START_REF] Woodruff | Know your customer: New approaches to understanding customer value and satisfaction[END_REF][START_REF] Shemwell | Customer-service provider relationships: An empirical test of a model of service quality, satisfaction and relationship-oriented outcomes[END_REF].

Our central emphasis is on fees. Fees are measured in this paper by whether or not a fee was charged, for each service type. Business Link services cover eleven main fields, corresponding to government specifications of service requirements. However, in our survey the frequency of use of some of these services is too small to provide valid estimates. For this reason our analysis mainly focuses on the five most frequently used service categories: provision of general information and advice, PBAs, sales and marketing advice, training and Investors in People (IiP) accreditation, and grants. These services account for about 70% of total use and provide strong contrasts of fee potential between low intensity (information) and high intensity services (PBAs, training/IiP), with marketing and grants as intermediate categories of intensity. Each client is asked to state whether a fee is charged for the specific service they have used for the particular Business Link involved. This captures the variation in Business Link operators as to whether any individual field of service is charged or not, and whether it was charged on this occasion.

In addition, we use controls for the difference between types of SME since other studies show there to be significant sources of variation in the take-up and evaluation of external business advice by different types of SME (see e.g. [START_REF] Storey | Understanding the small business sector[END_REF][START_REF] Bennett | The use of external advice by SMEs in Britain[END_REF]. The variables used, with the prior expectation of their effects, are: SME size: number of employees. Larger firms may experience higher impact and satisfaction as a result of their higher internal personnel capacity to make use of advice and control its delivery. SME profitability: declared pre-tax per employee. More profitable firms are more likely to be willing to pay for advice and hence may be more easily satisfied when a fee is charged.

Skill level: the proportion of the workforce with higher or intermediate skill levels. Higher skills should allow advice to be better used internally and better controlled to fit needs; this may also lead to advice being sought which is more targeted or technically more sophisticated.

Innovation record: (0/1) dummy for firms that have "introduced an innovation that is new to the firm or industry in the previous 3 years". This is the response to a specific question in the survey on the respondent's innovation record. Innovating firms may have higher impact and satisfaction as a result of more targeted needs.

Sector: (0/1) dummy for manufacturing compared to services. We have no prior expectations for the influence of sector.

In addition, the number of staff in the local Business Link is used to control for scale differences between different Business Link local bodies, which have differing emphases on intensive or extensive services evident in their varied staff ratios. Larger staff resources should increase the scope for higher impact and satisfaction as a result of the greater expertise available.

A further difference between Business Links used in the analysis is a categorical variable for the type of franchisee. Since 2001 Business Link services have been delivered by local franchisees who are local operators that bid for contracts from government to run the services under the Business Link brand. Under their government contract, franchisees must act as independent bodies with the franchise as their "only line of business". However, franchisees are of various types: some are 24), some are linked to local chambers of commerce (10), some are linked to other local bodies (7), and two are private sector companies.

Although they are all arms' length of related organisations and they must work to a standardised contract, the type of franchisee is expected to make a difference to the management of the franchise, and how this affects referrals and links to other service providers. This is likely to affect user experiences and the fee propensity. A categorical variable for franchise type is included in the analysis to assess the influence of this factor. It is expected that provision by chambers of commerce or private sector companies may increase impact and satisfaction, as their management may be closer to business needs compared to independent franchisees. Franchises linked to these bodies may also gain positive benefits through referral to other services provided by that franchisee compared to independent franchisees.

Service type and fees

The previous discussion has indicated strongly that the type of service and its intensity may be strong correlates of whether a fee can be charged. Indeed, the design of Business Link recognised that a key determinant of fee-raising potential was likely to be the intensity of service provided. Each service field offers different opportunities to Business Link operators, and even low intensity information provision may be charged for if an operator is prepared to do so and the client is prepared to agree to pay. However, two of the services fields we examine are expected to have the highest propensity to charge fees: PBAs and IiP.

Personal Business Advisers (PBAs) attempt to maintain a detailed and longer-term involvement of advisors as consultants to SMEs and this can increase their potential to charge fees. This was recognised at the outset of Business Link and formed a critical part of the original design. Intensive and long-term client relationships ("repeat business" and "client account management") were key concepts in the original Prospectus (DTI, 1992a). The focus on intensive counselling and fee targets were mutually self-reinforcing. They led to the foundation of the concept of a PBA as a core part of Business Link services. PBAs were to become expert 'account managers', seeing a SME client through various stages of development over many years. The PBA also became a key part of the way in which fee income could be Given these expected variations between our five service fields, it is first important to test the interrelationship of service type and fees. This is undertaken in Table 1, which shows the simple logit estimate of whether a fee is charged or not, related to service type, controlling for other variables.

These results are very informative. They indicate that fee intensity does not systematically vary with most SME characteristics, nor is it influenced by the different types of franchisee. The critical determinant of fees is the type of service.

As expected, SMEs are much more likely to experience a fee when they use one of the two intensive services of PBAs and training/IiP assessment, but the medium intensity service of sales and marketing advice also has a significant relation to fee raising. This is in comparison with the base case of information provision, which is a very low intensity service which is expected rarely to carry a fee. Interestingly, advice that leads to obtaining a grant does not bear a higher chance of experiencing a fee than the base case. These results confirm the general expectation that fees are charged in an opportunistic fashion, where the service experience allows it. The only SME characteristic that influences the propensity to charge a fee is the growth history of the SME. Companies that have declined in employment over the previous three years are less likely to be charged a fee. This suggests either a managerial response by Business Link that makes them more reluctant to charge a fee for SMEs that are in The interaction between fee charging and service type suggests that these have to be treated carefully in subsequent estimation. For this reason instrumental variables (IV) estimation is used below. IV estimation allows the interaction between independent variables and the error term to be removed. It requires an instrument that is meaningful and that is strongly correlated with both X and Y variables and is independent of the errors.

The correlation matrix between the main variables is shown in Table 2. This shows that the age of the firms is a strong contender for use as a IV: it is strongly intercorrelated with firm size and with use of fees, service type, impact and the other variables. This suggests that it is a suitable IV. The estimates are developed below first for impact and then for satisfaction.

Impact

The IV model for impact is shown in Table 3. This shows both anticipated and some surprising results. No characteristics of the business itself have significance on the level of impact that a SME experiences, and for the case of firm growth, profitability, skill level and innovation, the signs are in the opposite direction of those expected.

These results do, however, tend to confirm that fee charging propensity (and its likely impact) are opportunistic rather than systematic by firm type.

Our main focus is on Business Link aspects. The IV estimates here are in line with expectations. The franchisee is a highly significant influence, increasing impact assessments compared with independent franchisees by over one rating level (from moderate to important) in the case of chambers of commerce, and for franchises that are linked to other bodies. This confirms that links to other bodies provide benefits of greater impact, which probably results from greater tendency for referral, potential for economies of scale and scope, or the opportunity for a stronger private sector-led client focus. Impact is strongly influenced by the service fields used, as expected. The use of PBAs, training/IiP and sales and marketing advice is significantly likely to increase impact compared to business information. But the use of grants does not significantly increase impact, though the sign is in the expected positive direction.

There is, however, no evidence that fees increase the perceived impacts received from government advice services after controlling for other variables in the equation.

Impact appears to be chiefly strongly associated with the type of service provider and the service field and is largely independent of the type of SME and fee charging.

Service providers that are linked to the delivery of other services to SMEs, or have a stronger private sector focus, are more likely to receive higher impact ratings.

Satisfaction

The estimates of the IV model for client satisfaction are shown in Table 4. Our key variable, fee charging, again shows no significant relationship with satisfaction. This indicates that there is no relation of increased client evaluation from using fees. There is thus no indication of improved commerciality of the advisors/managers of Business Link resulting from fee charging, as hoped by Government objectives.

Firm type and service type have little effect on satisfaction. For the service fields this is a surprise. It had been expected that satisfaction would reflect some of the scope for intensification provided by different service types. However, if differences of intensity are occurring, as they must between the base case of information provision and the more intensive services of PBAs and training/IiP, then this is not influencing satisfaction.

Instead the main influence on satisfaction is the type of franchisee. Chamber of commerce and other partner organisations that operate Business Link franchises both have significantly higher satisfaction scores than the base case of independent franchisees. Again, we believe this is likely to arise mainly from the enhanced scope for effective referral between the Business Link and the other bodies and from their stronger client focus as a result of their private sector status. Although we cannot be certain about the causes of these higher levels of satisfaction, it is clear that for the The overall scale of the franchise, in terms of staff resources, is also a highly significant positive influence. This is to be expected since greater staff resources should lead to a greater capacity for client care. There are considerable differences in size of local Business Links, which may influence the economies of scale and scope in service delivery. Overall staff size varies, for example, varies from 14 to 136 across the system (mean 61.9), which gives very varied scope for scale economies, whilst staff per £m of turnover varies from 3.8 to 22.3 (mean 11.9), which shows wide variations of in-house service intensity and delivery strategy.

The variables used to control for the influence of differences in the SMEs themselves show few significant effects. Innovation and profitability each have a weakly significant relationship, but this is negative. These relationships may reflect SME capacity in a reverse way to that expected. As innovation and profitability increase this may increase need, but make the needs identified by the SME more specific and difficult to satisfy. Skill level, growth and firm size although not signifcant, however, are positive influences on satisfaction, as expected, reflecting the greater capacity of larger and more skilled firms to better design their advice requests and/or a greater capacity to manage the advice process to gain the greatest satisfaction from it.

Implications and Conclusion

This paper has sought to fill a gap in the literature of policy assessment for government support to SMEs: the effect of fee charging on SME assessments of government-supported advisory services. It has done this through analysis of the unique strategy developed for Business Link in Britain, that fees are expected to contribute an important part of the client experience (initially targeted first at 100% of income, subsequently reduced to 25%, and now sought where opportunities offer).

Fees were sought as a policy goal in part to reduce the burden on public finances and in part because it was believed that customers more highly value the services they pay for. This was sought as a means to make government advisory services more However, the use of fees is left to local managers and advisors to determine, and is thus 'opportunistic' in each case.

The paper has focused on the impact and satisfaction of SME clients with the services they received and whether they did or did not pay a fee. The impact assessments show that the nature of the provider is significant: chambers of commerce and other bodies that take on Business Link contracts achieve significantly higher impact and satisfaction than independent franchisees. Their staff size is also an important influence on satisfaction. However, our assessment shows that where opportunities are used by local Business Link managers/advisors to charge a fee, this has no significant relation with either impact or satisfaction, once service type is controlled for. A further important result is the very limited influence of any SME characteristics on impact or satisfaction.

Client evaluation thus appear to be largely independent of the type of firm. This confirms many earlier analyses of Business Link, and indeed other advice delivery, which suggests that advice is a very specific service requirement tailored to each individual firm's need not their generic characteristics (e.g. [START_REF] Hill | Differences in the consumer decisions process for professional vs. generic services[END_REF][START_REF] Woodruff | Know your customer: New approaches to understanding customer value and satisfaction[END_REF][START_REF] Shemwell | Customer-service provider relationships: An empirical test of a model of service quality, satisfaction and relationship-oriented outcomes[END_REF]Bennett andRobson, 1999, 2005).

There are some important conclusions to be drawn from these results. First, the major influence of service type on impact shows an interrelation with service intensity, as expected. However, the relationship is inverse: the coefficients relating to service field decline as service intensity increases, being strongest for sales and marketing, then for PBAs and then for training/IiP. This suggests that Business Link is best when it tries to do least! Although the more intensive services of PBAs and training/IiP have significant influences on impact this is lower than for less intensive sales and marketing advice process.

Second, the positive impact influences for these services suggests that many of earlier problems of Business Link, particularly of PBAs, are being overcome (see [START_REF] Hoc | Trade and Industry Committee, 5 th Report[END_REF][START_REF] Laforet | Assessing consultant quality for SMEs -the role of Business Links[END_REF]Mole, 2002a, b). This may in turn reflect the stronger accreditation process that has been developed for PBAs and training/IiP. However, the more strongly positive influence of sales and marketing advice is more surprising. This is a field where there is little professional training or qualifications available from professional institutes and thus where quality can be difficult to assure. The strong assessment for Business Link sales and marketing advice may reflect this less controlled market so that Business Link internal controls may be able to boost quality in an important field which is generally more suspect in its quality. These results, therefore, may indicate how the 'brand' of Business Link has now developed. It appears to be strongest for those services which have the strongest internal accreditation and quality controls.

Third, however, the lack of influence of type of service field on client satisfaction, suggests a tempering of any implications drawn for the different service fields. Thus whilst impact (which measures the value to the business) is influenced by service type as expected, the client satisfaction (which measures the quality or confidence in the form of service provision) appears independent of service field.

Fourth, for both impact and satisfaction, the nature of the provider is one of the strongest influences. Business Links provided by chambers of commerce, or linked to other organisations, appear significantly more able to improve impact and satisfaction than independent providers. Further research is clearly needed on how this improved performance is achieved. However, the likely implication is clear. An independent provider is more likely to retain clients in-house and has no benefits of economies of scope with other services it provides. In contrast chambers of commerce and other agents are already in the market supplying advice to SMEs. They are thus more likely to cross-refer clients to their other services, gain economies of scope from this other provision, and draw on their experience of dealing with SME clients to improve quality. There also appear to be economies of scale and scope for satisfaction as a result of larger staff numbers in some Business Link than others. We may also hypothesise, but it needs further testing, that the private sector ethos of chambers of commerce and other organisations makes them more likely to be customer focused.

Hence, this paper extends earlier findings with greater confidence [START_REF] Bennett | The Small Business Service: Business support, use, fees and satisfaction[END_REF], that the main influence on Business Link performance is management Fifth, the analysis has demonstrated that there is no significant influence of charging a fee on client evaluation. This is similar to earlier conclusions [START_REF] Bennett | The Small Business Service: Business support, use, fees and satisfaction[END_REF], which was able to assess the effect of fee size as well as fee propensity. The new results show similar results for fee propensity` from a larger and superior data set and undertaken with greater controls for the interrelation of service field and fee charging behaviour. The analysis also concerns a period when Business Link is fully established so that there should be no start up or transition effects in the structure of the system.

Sixth, the lack of any major influence of SME characteristics on client evaluations contrasts with many policy prescriptions to target advice on firms of a certain size, sector, growth history or innovation record, and conflicts with policy assessments that suggest that the smaller the SME the less able it is to use and evaluate the advice it receives.

These findings lead to four important policy implications. First, our major policy conclusion is that fee charging as an explicit and targeted policy was a mistake for Business Link. As we have shown, it has no influence on performance. There are no grounds for arguing that clients more strongly value Business Link services that are charged for. It is most important, therefore, that any residual incentives or rhetoric in favour of targeting fee revenues are removed. Although explicit targeting by the DTI has been removed since 2001, it is clear that many Business Link managers and advisors still remain strongly committed to fees. Moreover, the Chief Executive of the Small Business Service has still spoken in favour of measuring the benefits of advice to SMEs through the payback of the costs they pay [START_REF] Griffith | Delivering effective growth and support for small firms, Speech to QMW Public Policy Seminar[END_REF]. These residual commitments need to be eliminated. Third, satisfaction and impact will be significantly improved by developing provision in conjunction with broader-based service providers such as chambers of commerce or similar bodies. Independent, stand-alone providers provide significantly poorer client evaluations and need to be improved or phased out.

Fourth, for advisory bodies in other countries, our results show that fee income does offer some scope to mitigate government costs, but a fee strategy should only be contemplated as offering opportunistic and limited opportunities. Any emphasis on fees as targets should be avoided, as it can be severely distortionary to both managers and advisors, and will offer no improvements in client evaluations.

F

  of users paying a fee, assessment of their effects on clients is long overdue. The rest of this paper seeks to provide such an assessment.AssessmentThis paper uses information from two surveys. The first survey is a survey of how SMEs use Business Link. This derives from the University of Cambridge ESRC Centre for Business Research (CBR) survey of SMEs. The wave of this survey used is for 2002. Some comparisons are also drawn from earlier CBR surveys. Full detail of this survey is given in

  rate of employment growth 1999-2002. Growth is expected to have a positive relation with impact and satisfaction since it may be a surrogate for need which allows better focused requests for advice.

  PBAs being given personal targets for their fee earnings that were passed down from the government's targets for fee raising. It was hoped that through PBAs the value of services would be more readily seen and clients would be more willing to pay.Investors in People (IiP) is also an intensive service with strong fee potential. It aims to stimulate manager and employee commitments to training, The IiP standard emphasises the acquisition of formal employee and manager qualifications and provides a formal framework of accreditation as part of the government's strategy to improve "the growth capability of UK businesses …. by raising performance across a range of areas, such as: management skills, workforce development, use of innovation and adoption of best practice across different business functions" (DTI, 2003; see alsoDTI, 1992a).

  that declining SMEs are less willing to pay a fee and/or they seek services that are less able to support fees.

  is bound into a complex local management and delivery process where franchise type is very important to the how opportunities to charge a fee are used, and the effect this has on client experience.

  in culture and hence improve client assessments.

  . But this paper allows us to conclude that differences in franchise type are a major influence on this manager and advisor performance.

  Second, Business Link should focus on what it does best: basic information provision with minimal or no fee, sales and marketing advice, and intensive counselling/advice in fields where it can quality assure its advisor outcomes (particularly PBAs and ). It can, therefore, enhance its brand and client satisfaction by a more focused approach.

Page 10 of 28 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

  exchange that occurs between the client and adviser. Hence, it is a very effective means of assessing how far Business Link advisers provide a convincing, helpful and efficient service. It is particularly appropriate for services with a high intensity or high technical content where clients may not have the skills or resources to evaluate output in other more objective ways

	Submitted Manuscript
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Table 1 :

 1 Multivariate estimates of coefficients in a logit model of whether a fee was charged, standard errors in parentheses. (*** p <0.01; ** p < 0.05; * p < 0.1). The excluded categories are: for the type of BL services, business information; for franchisee, independent.

	o r
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25 of 28 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript F o r P e e r R e v i e w

		Firm age	Firm size	Growth Profitability	Skill level	Innovation Sector	BL staff Impact Fee	PBA	Sales	Training Grants Exporter
	Firm age	1.0000
	Firm size	0.4425	1.0000
	Growth	-0.5622	-0.2312	1.0000
	Profitability	0.1154	-0.1039	-0.0202	1.0000
	Skill level	-0.3396	-0.0899	0.3372	0.1084	1.0000
	Innovation	0.1888	0.1984	-0.1946	0.1039	0.0614	1.0000
	Sector	0.3783	-0.0412	-0.2831	0.0245	-0.5727	0.0915	1.0000
	BL staff no.	0.1363	0.0535	-0.1381	-0.1876	-0.2178	-0.0799	0.2202	1.0000
	Impact	0.1634	-0.1662	0.0880	0.0435	-0.0533	-0.1322	0.0326	0.0476	1.0000
	Fee	-0.1215	0.0828	-0.1033	-0.0380	-0.0221	0.0803	0.0038	-0.0354	0.1052	1.0000
	PBA	0.1411	-0.1406	0.0283	-0.0145	0.0270	-0.0104	0.0222	-0.0465	0.1294	0.0613	1.0000
	Sales	0.1431	0.0078	0.0132	0.0292	-0.0757	0.0077	0.0367	-0.0308	0.0420	0.1028	-0.1358	1.0000
	Training	-0.1717	0.1725	0.0359	0.0157	0.1005	-0.0360	-0.1733	-0.0552	0.0053	0.1727	-0.2432	-0.1896	1.0000
	Grants	-0.1297	0.0420	0.0048	-0.0143	-0.0541	0.0034	0.0484	0.0762	0.0213	-0.0418	-0.1999	-0.1558	-0.2792	1.0000
	Exporter	0.1750	0.0896	-0.2570	-0.1120	-0.0491	0.2475	0.2120	0.0211	-0.0008	0.1137	0.0678	0.0616	-0.0739	-0.0013	1.000
									26

Table 2 :

 2 Correlation matrix of main variables

Page 26 of 28 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

				Submitted Manuscript
			Impact
	Number	of	0.058
	Employees		(0.230)
	Employment		-0.001
	Growth		(0.002)
	Profitability	per	-0.016
	employee		(0.016)
	Skill		-0.214
			(0.489)
	Innovator		-0.237
			(0.240)
	Manufacturing/		-0.069
	Services		(0.281)
	Number of BL	-0.002
	employees Chamber of commerce franchise Other organisation	(0.006) F 0.516 ** (0.245) o r 0.683 **
	franchise Fee charged PBA Sales and Marketing		(0.340) 2.544 (1.692) 0.936 ** (0.468) 1.369 ** (0.662)	P e e r
	Training and IiP Grants Constant	0.971 * (0.554) 0.448 (0.342) 2.623 ***	R e v
	F (14,270) Root MSE N		(0.847) 0.86 1.75 285	i e w

Table 3 :

 3 Multivariate estimates of coefficients of instrumental variable estimates of the client assessments of impact using standard errors in parentheses. (*** p <0.01; ** p < 0.05; * p < 0.1). The excluded categories are: for the type of BL services, business information; for franchisee, independent.

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Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript


Mathematical and Quantitative Methods, F31 -Foreign Exchange < F3 -International Finance < F -International Economics, F14 -Country and Industry Studies of Trade < F1 -Trade < F -International Economics

Keywords: J-curve, trade balance, cointegration, causality, sstability

A deficit in the trade balance of a country may be eliminated by a real devaluation in the domestic currency. Success of devaluation, however, depends on whether or not the sum of import and export elasticities exceeds unity, which is also known as the Marshall-Lerner (ML) condition. Bahmani-Oskooee (1985) argued that there has been cases under which the ML condition was satisfied yet the trade balance continued to deteriorate. Therefore, he concludes that the focus of a trade policy should be on the short-run dynamics that trace the post devaluation time path of the trade balance implying the J-curve phenomenon. The J-curve effect suggests that the trade balance of a nation initially worsens after a real depreciation of the home currency, and then it gets better. Krueger (1983) has argued that at the time an exchange occurs, goods, which are already in transit and under contract, have been purchased, and the completion of those transactions dominates the short-term change in the trade balance. Arndt and Dorrance (1987) indicates that this so called J-curve effect occurs if the domestic currency prices of exports are sticky. There has been growing interest in the J-curve phenomenon in the last three decades. Bahmani-Oskooee and Ratha (2004a) provides a very comprehensive survey on the J-curve literature for the period of 1973-2003 from thirtyseven articles. The recent examples of the J-curve studies include Bahmani-Oskooee and Ratha (2004b), Bahmani-Oskooee et al. (2005), Hacker and Hatemi (2004), Narayan (2004), and Narayan and Narayan (2004). The empirical literature on the evidence of the J-curve, however, is fairly ambiguous.

In regards to the empirical evidence for the Turkish J-curve, one can identify readily a few previous studies with inconclusive results. Rose (1990) finds that the real exchange rates have no impact on the trade balance.

exchange regime, the TL has been steadily appreciating against the major world currencies in real terms since 2002. This situation is being attributed to excess real domestic interest rates that are intentionally set at high levels to prevent inflation rising again. As a direct consequence of the overvalued TL, the current account deficit, which stems largely from the trade account deficit, has currently exceeded 6% of that Turkish GDP. Ertugrul and Selcuk (2001) provides a detailed account of the causes and consequences of the Turkish twin deficits in the 1980s and 1990s. A similar account of the Turkish economy beyond 2000 is given in Akyurek (2006).

The motivation of this study is three fold: persistent balance deficits of Turkey since the 1980s provide a good rationale to revisit the J-curve phenomenon; data quality and its span is now far superior than the previous studies relating to Turkey; finally, the cointegration procedure in this paper has been used for many countries in testing the Jcurve phenomenon, except for Turkey.

The objectives of this study are as follows: i) to investigate the existence of the J-curve phenomenon both in the short-run and long-run using recent advances in time-series econometrics; ii) to establish the direction of causal relationships between trade balance, real effective exchange rates, foreign and domestic incomes variables; and iii) to implement parameter stability tests of Brown et al. (1975) to ascertain stability or instability in the trade balance model. The remainder of this paper is organized as follows. Section II describes the study's model and methodology. Section III discusses the empirical results, and finally Section IV concludes. The trade balance model employed in this study adopted the form of Rose and Yellen (1989) and it takes the following long-run (cointegrating) form: (1) where the measure of the trade balance, TB is the ratio of imports to exports; REER is the real effective exchange rate; YW is the industrial production index of industrial countries; YT is the industrial production index of Turkey. Ln is the natural logarithm transformation and t is the random error term. According to the J-curve phenomenon, it is expected that 0 1 < a since an increase in real effective exchange rate initially reduces the demand for the home country's export but increases its demand for imports.

II. THE MODEL AND METHODOLOGY

t
As a result, the balance of trade worsens initially but it will improve after a while as export and import volumes adjust to price changes. While there are no priori expectations about the signs of 2 a and 3 a , however, one asserts tentatively that 2 a is negative and 3 a is positive.

On investigating the cointegrating trade balance model with a view of testing the Jcurve phenomenon, several econometric methods were implemented in the last two decades. In regards to univariate cointegration approaches, there are several examples including Engle-Granger (1987) and the fully modified OLS procedures of Phillips and Hansen's (1990). In terms of multivariate cointegration, Johansen (1988), Johansen and Juselius (1990), and Johansen's (1996) full information maximum likelihood procedures are widely employed. See Bahmani-Oskooee and Ratha (2004a) for a full account of the econometric procedures applied in the J-curve studies. A recent single cointegration approach, known as autoregressive-distributed lag (ARDL) of Pesaran and Shin (1999) and Pesaran et al. (2001), has become popular amongst the researchers. Pesaran et al., cointegration approach, also named as bounds testing, has certain econometric advantages in comparison to other single cointegration procedures.

Firstly, endogeneity problems and inability to test hypotheses on the estimated coefficients in the long-run associated with the Engle-Granger method are avoided.

Secondly, the long and short-run parameters of the model in question are estimated simultaneously. Thirdly, all variables are assumed to be endogenous. Fourthly, the econometric methodology is relieved of the burden of establishing the order of integration amongst the variables and of pre-testing for unit roots. The ARDL approach to testing for the existence of a long-run relationship between the variables in levels is applicable irrespective of whether the underlying regressors are purely I(0), purely I(1), or fractionally integrated. Finally, according to Narayan (2004), the small sample properties of the bounds testing approach are far superior to that of multivariate cointegration.

An ARDL representation of equation ( 1) is formulated as follows: Once a long-run relationship has been established, equation ( 2) is estimated using an appropriate lag selection criterion. At the second stage of the ARDL cointegration procedure, it is also possible to perform a parameter stability test for the selected ARDL representation of the error correction model.

t t t t t m i m i m i i t i m i i t i i t i i t i t v YT a YW a REER a TB a YT a YW a REER a TB a a TB + + + + + + + + + = = = = = 1 8 1 7 1 6 1 5 1 0 0 4 0 3 2
A general error correction model (ECM) of equation ( 2) is formulated as follows:

t t k i i t i k i k i k i i t i i t i i t i t u EC YT b YW b REER b TB b b TB + + + + + + = = = = = 1 0 4 1 0 0 3 2 1 0 ln ln ln ln ln (3)
where is the speed of adjustment parameter and EC is the residuals that are obtained from the estimated cointegration model of equation (1).

The Granger representation theorem suggests that there will be Granger causality in at least one direction if there exists a cointegration relationship among the variables in equation ( 1), providing that they are integrated order of one. Engle-Granger (1987) indicates the Granger causality test which is conducted via a first difference vector autoregressive (VAR) will be misleading in the presence of cointegration. Therefore, an inclusion of additional variable to the VAR system such as the error correction term would help us to capture the long-run relationship. EC t-1 is the error correction term, which is derived from the long-run relationship, and it is not included in equation ( 4) if one finds no cointegration amongst the variables in question.

The existence of a cointegration derived from equation (2) does not necessarily imply that the estimated coefficients are stable as argued in Bahmani-Oskooee and Brooks (1999). Therefore, stability tests of Brown et al. (1975), which are also known as cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests based on the recursive regression residuals, may be employed to that end. These tests also incorporate the short-run dynamics to the long-run through residuals. The CUSUM and CUSUMSQ statistics are updated recursively and plotted against the break points of the model. Providing that the plot of these statistics fall inside the critical bounds of 5% significance, one assumes that the coefficients of a given regression are stable. These tests are usually implemented by means of graphical representation.

IIII. THE EMPIRICAL RESULTS

Quarterly data over 1980I-2005IV period were used to estimate equation (2). Data definition and sources of data are cited in the appendix. Equation (2) was estimated in two stages. In the first stage of the ARDL procedure, the order of lags on the firstdifferenced variables for equation (2) was obtained from unrestricted VAR by means of indicated the optimal lag level as four and six quarters respectively for this study. The results of this stage are not reported here for brevity. Then an F deletion test was applied to equation (2) in order to test the existence of a long-run relationship by using lags from four to six on following Bahmani-Oskooee and Goswami (2003). As they have shown that the results of this stage are sensitive to the order of VAR. Equation (2) was also estimated three more times in the same way but the dependent variable each time was replaced by one of the explanatory variables in search of other possible longrun relationship in any other form than it had already been described in equation (1).

The summary results of bounds tests are presented in Table 1. Table 1 indicates only one plausible a long-run relationship in which lnTB is dependent variable.

[ INSERT TABLE 1 ABOUT HERE]

In the second stage of ARDL cointegration procedure, equations (2) and (3) were estimated respectively on the basis of AIC and SBC criteria with six lags in search of selecting best-fitted model. The results of the model selection stages are reported in As far as the ECMs are concerned, it can be seen from Table 3 that the results of equation ( 3) are also very close in both model selection criteria. The long-run and short run results of the SBC version of the trade balance model, however, provide again relatively better results in terms of the expected signs and econometric diagnostics. The speed of adjustment coefficient, -0.35 is considerably low indicating a slow convergence to equilibrium in the case of a shock to the cointegrating relationship and that long-run equilibrium is attained only after three quarters. Based on the AIC and SBC results, however, one can suggest that there are no J-curve effects both in the long and short-runs since the coefficient of the real effective exchange rates does not alter from positive to negative in either case. Considering that the focus of this paper is essentially on the dynamics of devaluation, the impact of the lags of the real exchange rates on the trade balance from error correction version of the SBC model was estimated. The results are reported in Table 4. The evidence of the J-curve is now apparent in the REER variable as the positive coefficients are followed by the negative coefficients. This pattern of the coefficients shows an initial deterioration followed by an improvement in the trade balance.

[INSERT TABLE 4 ABOUT HERE]

Granger causality test requires that all variables are in equation ( 1) should be in integrated of order one. To this end, the traditional unit root tests such as the augmented Dickey andFuller (1979, 1981) and the Phillips and Peron (1988) were employed. The 10 unit root test results suggest that all variables in their first level differences are I (1). For brevity of presentation, they are not reported here either. Given the results of the bounds test in Table 1, Granger causality test was conducted to equation (4) as such that only the trade balance vector was estimated with an error correction term. Similarly the Granger causality tests were applied to other models without the error correction terms since one could not ascertain any long-run relationship for the other vectors.

Table 5 summarises the results of long-run and short-run Granger causality.

[INSERT TABLE 5 HERE]

On considering the long-run Granger causality, one suggests that the lagged error correction term is statistically significant which also confirms the results of the bounds test. The speed of the adjustment, however, is less than the ARLD estimations suggesting that the long-term convergence to equilibrium will take longer. Granger causality runs interactively via both exchange rates and world income to trade balance ratio. In regards to the short-run Granger causality, one sees that there exists a bidirectional Granger causality between exchange rates and trade balance ratio, implying that as the trade balance improves it causes a real appreciation of the TL. Likewise, a real depreciation will have a positive impact on the trade balance. There are, however, uni-directional Granger causalities, which run from world income to the trade balance, from world income to domestic income, and from exchange rates to domestic income. 2) and the long-run impact of equation (1). Equation (3) was estimated by ordinary least squares with a lag length of four based on the SBC criterion. Figure 1 and 2 provides the plots of CUSUM and CUSUMSQ tests respectively. Figure 1 and 2 present conflicting results in regards to the parameter stability tests. Whilst the former test indicates instability the later suggests stability in the parameters of the trade balance equation.

IV. CONCLUSION

This study has attempted to estimate the J-curve phenomenon through a reduced form trade balance model in search of providing fresh empirical evidence in the case of Turkish data. A recent single cointegration technique proposed by Pesaran et al. (2001) was employed to investigate the short-run and long-run responses of the trade balance to currency depreciation. The results from bounds tests have indicated only one possible long-run relationship in which the trade balance is the dependent variable. In contrast to the results of the previous results relating to Turkey, one finds no long-run impact of a real devaluation on the trade balance but there exists the J-curve phenomenon in the short-run. Whilst, in the long-run, real effective exchange rates and world income Granger cause to the trade balance, in the short-run there is a feedback relationship between the real effective exchange rates and trade balance. The parameter stability tests on the long-run trade balance equation appear to be inconclusive. The relevant critical values are obtained from Table C1.iii (with an unrestricted intercept and no trend with three regressors) in Pesaran et al. (2001).* indicates the statistical significance at the 5 % level. The optimal lag length is four.

APPENDIX

F

Plot of Cumulative Sum of Recursive Residuals

The straight lines represent critical bounds at 5% significance level Hacker and Hatemi (2004), Narayan (2004), and Narayan and Narayan (2004). The empirical literature on the evidence of the J-curve, however, is fairly ambiguous.

In regards to the empirical evidence for the Turkish J-curve, one can identify readily a few previous studies with inconclusive results. Rose (1990) finds that the real exchange rates have no impact on the trade balance. The work of Bahmani-Oskooee Turkey has adopted a policy of trade liberalization since 1980 and has pursued a successful export-led growth policy. The ratio of total exports to gross domestic product (GDP) increased from 4.1 to 13.3 percent during the period 1980-1988 and the real GDP grew by 5.8 percent in the same period. In 1989, there was a policy reversal, which slowed the depreciation of the Turkish lira (TL), in part to control inflation, but mainly to be able to easily borrow from the domestic markets, which led to five recessions in 1989, 1991, 1994, 1999, and 2001. The recessions of 1991, 1994and 2001 were preceded by substantial increases in the real exchange rates. The impacts of devaluations on the trade balance, however, seem to be short lived as the early improvements in the trade balance are reversed steadily after a while. To combat the spiralling twin deficits in 2001, the IMF-led stabilization policy was put into effect once more. As a result, the internal imbalance has improved considerably but at the exchange regime, the TL has been steadily appreciating against the major world currencies in real terms since 2002. This situation is being attributed to excess real domestic interest rates that are intentionally set at high levels to prevent inflation rising again. As a direct consequence of the overvalued TL, the current account deficit, which stems largely from the trade account deficit, has currently exceeded 6% of that Turkish GDP. Ertugrul and Selcuk (2001) provides a detailed account of the causes and consequences of the Turkish twin deficits in the 1980s and 1990s. A similar account of the Turkish economy beyond 2000 is given in Akyurek (2006).

The motivation of this study is two fold: persistent trade balance deficits of Turkey since the 1980s provide a good rationale to revisit the J-curve phenomenon and the cointegration procedure in this paper has been used for many countries in testing the Jcurve phenomenon, except for Turkey.

The objectives of this study are as follows: i) to investigate the existence of the J-curve phenomenon both in the short-run and long-run using recent advances in time-series econometrics; ii) to establish the direction of causal relationships between trade balance, real effective exchange rates, foreign and domestic incomes variables; and iii) to implement parameter stability tests of Brown et al. (1975)

II. THE MODEL AND METHODOLOGY

The trade balance model employed in this study adopted the form of Rose and Yellen (1989) and it takes the following long-run (cointegrating) form:

t t t t t YT a YW a REER a a TB + + + + = ln ln ln ln 3 2 1 0 (1)
where the measure of the trade balance, TB is the ratio of imports to exports; REER is the real effective exchange rate; YW is the industrial production index of industrial countries; YT is the industrial production index of Turkey. Ln is the natural logarithm transformation and t is the random error term. According to the J-curve phenomenon, it is expected that 0 1 < a since an increase in real effective exchange rate initially reduces the demand for the home country's export but increases its demand for imports.

As a result, the balance of trade worsens initially but it will improve after a while as export and import volumes adjust to price changes. While there are no priori expectations about the signs of 2 a and 3 a , however, one asserts tentatively that 2 a is negative and 3 a is positive.

On investigating the cointegrating trade balance model with a view of testing the Jcurve phenomenon, several econometric methods were implemented in the last two decades. In regards to univariate cointegration approaches, there are several examples including Engle-Granger (1987) and the fully modified OLS procedures of Phillips and Hansen's (1990). In terms of multivariate cointegration, Johansen (1988), Johansen andJuselius (1990), andJohansen's (1996) Firstly, endogeneity problems and inability to test hypotheses on the estimated coefficients in the long-run associated with the Engle-Granger method are avoided.

Secondly, the long and short-run parameters of the model in question are estimated simultaneously. Thirdly, all variables are assumed to be endogenous. Fourthly, the econometric methodology is relieved of the burden of establishing the order of integration amongst the variables and of pre-testing for unit roots. The ARDL approach to testing for the existence of a long-run relationship between the variables in levels is applicable irrespective of whether the underlying regressors are purely I(0), purely I(1), or fractionally integrated. Finally, according to Narayan (2004), the small sample properties of the bounds testing approach are far superior to that of multivariate cointegration.

An ARDL representation of equation ( 1) is formulated as follows: Once a long-run relationship has been established, equation ( 2) is estimated using an appropriate lag selection criterion. At the second stage of the ARDL cointegration procedure, it is also possible to perform a parameter stability test for the selected ARDL representation of the error correction model.

t t t t t m i m i m i i t i m i i t i i t i i t i t v YT a YW a REER a TB a YT a YW a REER a TB a a TB + + + + + + + + + = = = = = 1 8 1 7 1 6 1 5 1 0 0 4 0 3 2
A general error correction model (ECM) of equation ( 2) is formulated as follows:

t t k i i t i k i k i k i i t i i t i i t i t u EC YT b YW b REER b TB b b TB + + + + + + = = = = = 1 0 4 1 0 0 3 2 1 0 ln ln ln ln ln (3)
where is the speed of adjustment parameter and EC is the residuals that are obtained from the estimated cointegration model of equation ( 1).

The Granger representation theorem suggests that there will be Granger causality in at least one direction if there exists a cointegration relationship among the variables in equation ( 1), providing that they are integrated order of one. Engle-Granger (1987) caution that the Granger causality test, which is conducted in first difference via a vector autoregression (VAR) will be misleading in the presence of cointegration.

Therefore, an inclusion of additional variable to the VAR system such as the error correction term would help us to capture the long-run relationship. To this end, an [ ] EC t-1 is the error correction term, which is derived from the long-run relationship, and it is not included in equation ( 4) if one finds no cointegration amongst the variables in question. The Granger causality test may be applied to equation (4) as follows: i) by checking statistical significance of the lagged differences of the variables for each vector; this is a measure of short-run causality and ii) by examining statistical significance of the error correction term for the vector that there exists a long-run relationship.

+ + + = = t t t t t i t i t i t i t i i i i i i i i i i i i i i i i
The existence of a cointegration derived from equation (2) does not necessarily imply that the estimated coefficients are stable as argued in Bahmani-Oskooee and Brooks (1999). Hence, stability tests of Brown et al. (1975), which are also known as cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests based on the recursive regression residuals, may be employed to that end. These tests also incorporate the short-run dynamics to the long-run through residuals. The CUSUM and CUSUMSQ statistics are updated recursively and plotted against the break points of the model. Providing that the plot of these statistics fall inside the critical bounds of 5% significance, one assumes that the coefficients of a given regression are stable. These tests are usually implemented by means of graphical representation.

III. THE EMPIRICAL RESULTS

Quarterly data over 1980I-2005IV period were used to estimate equation (2). Data definition and sources of data are cited in the appendix. Equation (2) was estimated in two stages. In the first stage of the ARDL procedure, the order of lags on the firstdifferenced variables for equation (2) was obtained from unrestricted VAR by means of Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC), which indicated the optimal lag level as four and six quarters respectively for this study. The results of this stage are not reported here for brevity. Then an F deletion test was applied to equation ( 2) in order to test the existence of a long-run relationship by using lags from four to six on following Bahmani-Oskooee and Goswami ( 2003). As they have shown that the results of this stage are sensitive to the order of VAR. Equation ( 2) was also estimated three more times in the same way but the dependent variable each time was replaced by one of the explanatory variables in search of other possible longrun relationship in any other form than it had already been described in equation (1).

The summary results of bounds tests are presented in Table 1. Table 1 indicates only one plausible a long-run relationship in which lnTB is dependent variable.

[ INSERT TABLE 1 ABOUT HERE]

In the second stage of ARDL cointegration procedure, equations ( 2 Considering the long-run coefficients in the panel A of Table 2, one concludes that the SBC based trade balance model seems to be a slightly better fit than the AIC model since all the coefficients in the former model are statistically significant at the 5% level.

Apart from that difference, both model selection criteria reveal almost identical results.

[INSERT TABLE 3 ABOUT HERE]

As far as the ECMs are concerned, it can be seen from Table 3 that the results of equation ( 3) are also very close in both model selection criteria. The long-run and short run results of the SBC version of the trade balance model, however, provide again relatively better results in terms of the expected signs and econometric diagnostics. The speed of adjustment coefficient, -0.35 is considerably low indicating a slow convergence to equilibrium in the case of a shock to the cointegrating relationship and that long-run equilibrium is attained only after three quarters. Based on the AIC and SBC results, however, one can suggest that there are no J-curve effects both in the long and short-runs since the coefficient of the real effective exchange rates does not alter from positive to negative in either case. Considering that the focus of this paper is essentially on the dynamics of devaluation, the impact of the lags of the real exchange rates on the trade balance from error correction version of the SBC model was estimated. The results are reported in Table 4. The evidence of the J-curve is now apparent in the REER variable as the positive coefficients are followed by the negative coefficients. This pattern of the coefficients shows an initial deterioration followed by an improvement in the trade balance. Granger causality test requires that all variables are in equation ( 1) should be in integrated of order one. To this end, the traditional unit root tests such as the augmented Dickey andFuller (1979, 1981) and the Phillips and Peron (1988) were employed. The unit root test results suggest that all variables in their first level differences are I (1). For brevity of presentation, they are not reported here. Having a cointegrating relationship among [TB t , REER t , YW t , YT t ] on the basis of the results of the bounds test in Table 1, Granger causality test was conducted to equation ( 4) as such that only the trade balance vector was estimated with an error correction term. Similarly the Granger causality tests were applied to other models without the error correction terms since one could not ascertain any long-run relationship for the other vectors. Table 5 summarises the results of long-run and short-run Granger causality.

[INSERT TABLE 5 ABOUT HERE]

On considering the long-run Granger causality, one suggests that the lagged error correction term with the expected sign is statistically significant which also confirms the results of the bounds test. The speed of the adjustment, however, is less than the ARLD estimations suggesting that the long-term convergence to equilibrium will take longer. Granger causality runs interactively via both exchange rates and world income to trade balance ratio. In regards to the short-run Granger causality tests based on the F statistics, one sees that there exists a bi-directional Granger causality between exchange rates and trade balance ratio, implying that as the trade balance improves it causes a real appreciation of the TL. Likewise, a real depreciation will have a positive impact on the trade balance. There are, however, uni-directional Granger causalities, which run from world income to the trade balance, from world income to domestic income, and from exchange rates to domestic income.

[INSERT FIGURE 1 AND FIGURE 2 ABOUT HERE]

The parameter stability tests were implemented via equation (3), which captures the short-run dynamics of equation ( 2) and the long-run impact of equation (1). Equation (3) was estimated by ordinary least squares with a lag length of four based on the SBC criterion. Figure 1 and 2 provides the plots of CUSUM and CUSUMSQ tests, respectively. Figure 1 The relevant critical values are obtained from Table C1.iii (with an unrestricted intercept and no trend with three regressors) in Pesaran et al. (2001).* indicates the statistical significance at the 5 % level. The optimal lag length is four.

  external balance has got worse. Despite having the free-floating

  (AIC) and Schwarz Bayesian Criterion (SBC), which

[

  tests were implemented via equation (3), which captures the short-run dynamics of equation (

  Figure 1. Plot of CUSUM Plot of Cumulative Sum of Squares of Recursive Residuals

  1992), which is based on Almon lag structure on real exchange rate, has found no support for it either. On employing the Engle-Granger cointegration approach, Bahmani-Oskooee and Alse (1994) asserts that the long-run impact of devaluation on the trade balance model is positive.Brada et al. (1997) who divided the data set into two sub-samples reports no long-run relationship between the variables of the trade balance function in the 1970s but they have revealed reverse results for the 1980s.Kale (2001) points out that a real depreciation of the domestic currency helps to improve the trade balance with a lag of about one-year and the impacts of devaluations on the trade balance are positive in the long-run. In a recent study,Akbostanci (2004) also presents empirical evidence of the J-curve phenomenon in the long-run. As a passing note, one should point out that the last two studies are based on that ofJohansen-Juselius (1990) multivariate cointegration procedure with relatively short data spans derived from the 1980s and 1990s.

  external balance has got worse. Despite having the free-floating

  Granger causality test involving the error correction term is formulated in a multivariate pth order vector error correction model.

  ) and (3) were estimated respectively on the basis of AIC and SBC criteria with six lags in search of selecting best-fitted model. The results of the model selection stages are reported in

  and 2 display conflicting results in regards to the parameter stability tests. Whilst the former test indicates instability the later suggests stability in the parameters of the trade balance equation.IV. CONCLUSIONThis study has attempted to estimate the J-curve phenomenon through a reduced form trade balance model in search of providing fresh empirical evidence in the case of Turkish data. A recent single cointegration technique proposed byPesaran et al. (2001) was employed to investigate the short-run and long-run responses of the trade balance to currency depreciation. The results from bounds tests have indicated only one possible long-run relationship in which the trade balance is the dependent variable. In contrast to the results of the previous results relating to Turkey, one finds no long-run impact of a real devaluation on the trade balance but there exists the J-curve short-run. The existence of J-curve in the short-run confirms that the Turkish foreign trade balance deficit improves rather rapidly on following currency depreciations as it has happened in the TL depreciations of 1994, 1999 and 2004.Whilst, in the long-run, real effective exchange rates and world income Granger cause to the trade balance, in the short-run there is a feedback relationship between the real effective exchange rates and trade balance. The parameter stability tests on the long-run trade balance equation appear to be inconclusive.APPENDIXData definition and sourcesThe data set used in this study cover the period 1980I to 2005IV. All data are collected from International Financial Statistics, (IMF) and Central Bank of Turkey (CBT).TB is Turkey's trade balance. It is defined as the ratio of real imports to real exports.The raw data of exports and imports were deflated by the USA consumer price index. Source: IMF. REER is the real effective exchange rates index. Source: CBT.YW is industrial production index of industrial countries. Source: IMF.YT is industrial production index of Turkey. Source: IMF

Figure 1 .

 1 Figure 1. Plot of CUSUM

  and the other set assumes they are all I(1). If the computed Fstatistic exceeds the upper critical bounds value, then the H 0 is rejected. If the F-statistic falls into the bounds then the test becomes inconclusive. Lastly, if the F-statistic is below the lower critical bounds value, it implies no cointegration.

	all variables are I(0)
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	ln	0	1		ln								ln	ln i e	ln	(2)
	ln	ln									ln			ln	w
	Pesaran et al. cointegration procedure is briefly outlined as follows. The bounds testing
	procedure is based on the F or Wald-statistics and is the first stage of the ARDL
	cointegration method. Accordingly, a joint significance test that implies no
	cointegration, (H 0 :	a	5	=	a	6	=	a	7	=	8 a	=	0	), should be performed for equation (2). The F
															6

test used for this procedure has a non-standard distribution. Thus,

Pesaran et al.

compute two sets of critical values for a given significance level. One set assumes that

Table 2

 2

	and 3 respectively.
	[INSERT TABLE 2 ABOUT HERE]
	Considering the long-run coefficients in the panel A of Table 2, one concludes that the
	SBC based trade balance model seems to be a slightly better fit than the AIC model
	since all the coefficients in the former model are statistically significant at the 5% level.
	Apart from that difference, both model selection criteria reveal almost identical results.

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Table 2 .

 2 Long-run coefficients of the trade balance of Turkey Panel A: the long-run results H are Lagrange multiplier statistics for tests of residual correlation, functional form mis-specification, non-normal errors and heteroskedasticity, respectively. These statistics are distributed as Chi-squared variates with degrees of freedom in parentheses. * indicates statistical significance at the 5% level.

	Dependent variable TB ln
					Model Selection Criterion
	Regressors AIC ARDL (1,2,3,0)	SBC ARDL (1,1,3,0)
	ln	REER	0.468	(1.449)	0.656*	(2.068)
	ln	YW	-3.123* (2.326)	-3.440*	(2.477)
	ln	YT	1.328*	(2.371)	1.491*	(2.572)
	Constant	7.387	(2.081)	7.186	(1.989)
	Panel B: the short-run diagnostic test statistics
	2 SC (4)=2.324,	2 FC (1)=5.731	2 SC (4)=2.144,	2 FC (1)=4.948
	2 N (2)=8.176,	2 H (1)=0.206	2 N (2)=7.192,	2 H (1)=0.325
	Notes: The absolute value of t-ratios is in parentheses. 2 SC , 2 FC , 2 N , and 2

Table 3 .

 3 Short-run coefficients of the trade balance of Turkey-H are Lagrange multiplier statistics for tests of residual correlation, functional form mis-specification, non-normal errors and heteroskedasticity, respectively. These statistics are distributed as Chi-squared variates with degrees of freedom in parentheses. * indicates statistical significance at the 5% level.

	estimates from ECM
	Dependent variable	ln	t TB
								Model Selection Criterion
	Regressors		AIC ARDL (1,2,3,0) SBC ARDL (1,1,3,0)
		ln	t REER		0.907*	(3.759)	0.952*	(3.890)
		ln	t REER	1	0.494*	(2.044)	-	-
		ln	t YW			-2.323*	(4.011)	-2.225* (3.787)
		ln t YW	1		0.831	(1.276)	1.116	(1.723)
		ln t YW	2		2.845*	(5.138)	2.939*	(5.233)
		ln	t YT			0.467*	(2.525)	0.522*	(2.804)
	Constant			2.600	(2.251)	2.517	(2.143)
	EC	t	1			-0.351*	(4.938)	-0.350* (4.830)
	R	2					0.481	0.507
	F-statistics		14.168	15.287
	DW-statistics 2.034	2.041
	RSS				2.071	2.131

Table 5 .

 5 Results of Granger CausalityDependent Variable :* indicates statistical significance at the 5% level. The optimal length is 4 and is based on SBC.

				Submitted Manuscript
			ln	t TB	ln	t REER	ln	t YW	ln	t YT	1 EC (t-statistics) t
	ln	t TB	-		2.94*	4.82*	1.54	-0.26*
					(0.01)	(0.01)	(0.18)	(3.24)
	ln	t REER	3.32*	-		1.42	1.46	-
			(0.01)			(0.22)	(0.20)
	ln	t YW	0.79		0.65		-		2.18	-
			(0.55)	(0.66)			(0.06)
	ln	t YT	1.64		3.40*	2.97*	-	-
			(0.15)	(0.00)	(0.01)
	Causality inference: REER TB, YW TB, WY YT, REER YT

NotesPage 20 of 40 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

  cointegration approach, known as autoregressive-distributed lag (ARDL) ofPesaran and Shin (1999) andPesaran et al. (2001), has become popular amongst the researchers. Pesaran et al., cointegration approach, also named as bounds testing, has certain econometric advantages in comparison to other single cointegration procedures.

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full information maximum likelihood procedures are widely employed. See Bahmani-Oskooee and Ratha (2004a) for a full account of the econometric procedures applied in the J-curve studies. A recent single

  compute two sets of critical values for a given significance level. One set assumes that all variables are I(0) and the other set assumes they are all I(1). If the computed Fstatistic exceeds the upper critical bounds value, then the H 0 is rejected. If the F-statistic falls into the bounds then the test becomes inconclusive. Lastly, if the F-statistic is below the lower critical bounds value, it implies no cointegration.

				F o r
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															i e
	ln	ln	0	ln	1		ln					ln	ln	ln	ln w	ln	(2)
	Pesaran et al. cointegration procedure is briefly outlined as follows. The bounds testing
	procedure is based on the F or Wald-statistics and is the first stage of the ARDL
	cointegration method. Accordingly, a joint significance test that implies no
	cointegration, (H 0 :	a	5	=	a	6	=	a	7	=	8 a	=	0	), should be performed for equation (2). The F

test used for this procedure has a non-standard distribution. Thus,

Pesaran et al.

Table 2

 2

	and 3 respectively.

Table 2 .

 2 Long-run coefficients of the trade balance of Turkey H are Lagrange multiplier statistics for tests of residual correlation, functional form mis-specification, non-normal errors and heteroskedasticity, respectively. These statistics are distributed as Chi-squared variates with degrees of freedom in parentheses. * indicates statistical significance at the 5% level.

	Panel A: the long-run results
	Dependent variable TB ln
					Model Selection Criterion
	Regressors AIC ARDL (1,2,3,0)	SBC ARDL (1,1,3,0)
	ln ln	REER YW	0.468 -3.123* (2.326) (1.449)	0.656* -3.440*	(2.068) (2.477)
	ln	YT	1.328*	(2.371)	1.491*	(2.572)
	Constant	7.387	(2.081)	7.186	(1.989)
	Panel B: the short-run diagnostic test statistics
	2 SC (4)=2.324,	2 FC (1)=5.731	2 SC (4)=2.144,	2 FC (1)=4.948
	2 N (2)=8.176,	2 H (1)=0.206	2 N (2)=7.192,	2 H (1)=0.325
	Notes: The absolute value of t-ratios is in parentheses. 2 SC , 2 FC , 2 N , and 2

Table 3 .

 3 Short-run coefficients of the trade balance of Turkeyestimates from ECM Dependent variable : The absolute values of t-ratios are in parentheses. RSS stands for residual sum of squares. * indicates statistical significance at the 5% level.

						ln	t TB
						Model Selection Criterion
	Regressors		AIC ARDL (1,2,3,0) SBC ARDL (1,1,3,0)
	ln	t REER		0.907*	(3.759)	0.952*	(3.890)
	ln	t REER	1	0.494*	(2.044)	-	-
	ln	t YW			-2.323*	(4.011)	-2.225* (3.787)
	ln t YW	1		0.831	(1.276)	1.116	(1.723)
	ln t YW	2		2.845*	(5.138)	2.939*	(5.233)
	ln	t YT			0.467*	(2.525)	0.522*	(2.804)
	Constant			2.600	(2.251)	2.517	(2.143)
	EC	t	1			-0.351*	(4.938)	-0.350* (4.830)
	2 F-statistics R		0.481 14.168		0.507 15.287
	DW-statistics 2.034		2.041
	RSS				2.071		2.131

Notes

Table 4 .

 4 Coefficient estimates of H are Lagrange multiplier statistics for tests of residual correlation, functional form mis-specification, non-normal errors and heteroskedasticity, respectively. These statistics are distributed as Chi-squared variates with degrees of freedom in parentheses. * indicates statistical significance at the 5% level.

						ln	REER	t	i	and error correction term
	Dependent variable	ln	t TB
	Regressors		Coefficients t-statistics
		ln	t REER		0.890*	3.144
		ln	t REER	1	0.370	1.308
		ln	t REER	2	0.323	1.115
		ln	t REER	3	0.327	1.141
		ln	t REER	4	-0.094	0.319
		ln	t REER	5	-0.240	0.838
		ln	t REER	6	0.403	1.407
	Constant		-0.018	0.961
	EC	t	1		-0.327*	4.102
	R	2				0.421
	Diagnostic test statistics
	2 SC (4)=5.129	2 FC (1)=2.623,	2 N (2)=4.143,	2 H (1)=0.003
	Notes: t-ratios are in absolute values. 2 SC , 2 FC , 2 N , and 2

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Table 5 .

 5 Results of Granger Causality F statistics (probability) Dependent VariableCausality inference: REER TB, YW TB, YW YT, REER YT Notes:* indicates statistical significance at the 5% level. The optimal length is 4 and is based on SBC.

			ln	t TB	ln	t REER	ln	t YW	ln	t YT	t EC	1
											(t-statistics)
	ln	t TB	-		2.94* (0.01)	4.82* (0.01)	1.54 (0.18)	-0.26* (3.24)
	ln	t REER	(0.01) 3.32*	-		(0.22) 1.42	(0.20) 1.46	-
	ln	t YW	(0.55) 0.79	(0.66) 0.65	-		(0.06) 2.18	-
	ln	t YT	(0.15) 1.64	(0.00) 3.40*	(0.01) 2.97*	-		-

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

Data definition and sources

The data set used in this study cover the period 1980I to 2005IV. All data are collected from International Financial Statistics, IMF and Central Bank of Turkey (CBT).

TB is Turkey's trade balance. It is defined as the ratio of real imports to real exports.

The raw data of exports and imports were deflated by the USA consumer price index. Source: IMF.

REER is the real effective exchange rates index. Source: CBT.

WY is industrial production index of industrial countries. Source: IMF.

YT is industrial production index of Turkey. Source: IMF