• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.243-254
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• 2023

This study investigates the factors contributing to price fluctuations in the shipscrapping market, the final stage in a vessel's life cycle. Shipping companies make decisions on ship dismantling based on factors such as declining freight rates, increasing vessel age leading to higher costs, or compliance with new environmental regulations. Utilizing the FMOLS (Fully Modified Ordinary Least Squares) and VECM (Vector Error Correction Model) methodologies, the research explores the long-term elasticities of factors influencing shipscrapping prices and examines short-term causal relationships. Using a time series dataset spanning from December 2015 to April 2023, covering a total of 90 months, the study focuses on the shipscrapping prices of Capesize vessels in India and Bangladesh, which constitute a significant portion of the shipbreaking market. The findings indicate that, in the long term, shipscrapping prices are closely related to global scrap prices, 20-year-old secondhand Capesize vessel prices, newbuilding prices, and exchange rates. In terms of short-term causal relationships, an increase in global scrap prices induces a rise in shipscrapping prices, while the remaining variables do not contribute to such increases. Specifically, an escalation in shipscrapping prices is associated with increased prices of 20-year-old secondhand vessels, newbuilding prices, and exchange rates. However, the other variables do not show a significant influence on short-term increases in shipscrapping prices.

• Journal of Korean Society of Forest Science
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• v.80 no.1
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• pp.72-81
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• 1991

This study was carried out to provide necessary information for improving quarrying industry management in Korea. The results of the study are summarized as follows : 1. In aggregate and building-stone quarrying firms the managers over 40 years of age are 97% and 89.1%, the ones above education level of high school are 90% and 85% and the ones not more than 10 years of quarrying experience are 70% and 52%, respectively. Accordingly it can be pointed out that most of the managers of two types of firms are relatively old, have high educational background, while quarrying experiences of building-stone firm managers are longer than that of aggregate firm managers. 2. Most of the management forms are social corporation(60%) for aggregate quarry firms and private management(76%) for building-stone firms. Average areas of permitted stone-pits of aggregate and building-stone quarries are about 2.86ha and 1.66ha respectively. That is, aggregate quarrying firms are carried on a larger scale than building-stone quarrying firms. 3. The yearly average product of aggregate quarrying firms has increased steadily from $88.961m^3$ in 1985 to $144.028m^3$ in 1988, while, in case of building-stone quarry firms, it has significantly increased from $4.155m^3$ to $19.462m^3$ from 1985 to 1987, but reduced to $13.400m^3$ in 1988. Unstable production activities of building-stone quarrying firms may require continuous government support. 4. Major cost items are equipment rental, depreciation, salaries, repair, maintenance for aggregate quarrying firms, and salaries, depreciation, fuel, tax for building-stone quarrying firms. The yearly average rate of return is about 9.7% for aggregate quarry firms and 2.6% for building-stone quarry firms. It can be pointed out that aggregate quarrying firms is better managed than building-stone quarrying firms. 5. The production elasticity of salary for aggregate quarrying firms is 0.495, that of employees is 0.559, and that of capital service is 0.513. The sum of the elasticities is 1.257>1. Fur building-stone quarrying firms, that of employees is 0.492, that of variable costs is 0.192, and that of capital service is 0.498. The sum of elasticities is 1.172>1, thus denotes the increasing returns to scale for both types quarrying firms. 6. The ratio of marginal value product to opportunity cost of empolyees is 2.54, that of variable costs is 3.62, and that of capital service is 1.45, in aggregate quarrying firms. That of employees is 2.47, that is variable costs was 2.34, and that of capital service is 19.67 in building-stone quarrying firms. Therefore the critical factors for more expansion of management scale in aggregate quarrying firms are variable cost and employees, and are capital service in building-stone quarry ing firms. 7. The break-even points of stone sales are about 0.587 billion won and 0.22 billion won in aggregate and building-stone quarrying firms respectively. The optimum sales Level for profit maximization are about 2.0 billion and 0.5 billion in aggregate and building-stone quarry firms respectively.

• Journal of Korean Society of Forest Science
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• v.32 no.1
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• pp.29-35
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• 1976

In order to estimate sawmill productivities, rates of technical change and optimum combination of production factors, Cobb-Douglas production functions have been derived using data obtained from 96 sample mills in Busan-Incheon, southwestern and northeastern areas. The results may be summarized as follows: 1. There is a tendency of expanding average sawmill size in the areas. The horse-power holdings per mill have been increased at the rates of 91 percent in Busan-Incheon, 7.7 percent in southwestern and 16.9 percent in northeastern areas. This implies that the mills around log-importing ports have made rapid development, compared with those in forest regions. 2. The regression coefficients (production elasticities) of the functions for the year of 1967 in the above three areas are much similar each other, but significant differencies are found in the production functions of 1975. In other words, sawmill productivity was mainly restricted by capital deficiencies in all areas in 1967, but this situation was succeeded only by N-E area in 1975. The range of sum of regression coefficients is 1.0437-1.4214, this indicates increasing rates of return to scale. 3. The annual rates of technical changes in B-I, S-W and N-E areas for the observed period are 17.6, 7.6 and 2.2 percents respectively. Busan-Incheon is the only area where labor productivity is higher than that of capital. 4. The best combination of production factors for maximizing firm's profit is subject to the changes of input and output prices. With some assumptions of prices and costs, the optimum levels of power and labor input in B-I, S-W and N-E areas are 57:17, 427:94 and 192:27.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.24-31
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• 2009

Firms produce various products that differ by function, design, color, etc. Product proliferation occurs for three different reasons. When there exist economies of scope, the unit cost for a product is lower when it is produced in conjunction with another product than when it is produced separately. Second, consumers are heterogeneous in the sense that they have different tastes, preferences, or price elasticities. A firm can earn more profit by segmenting consumers into different groups with similar characteristics. For example, product proliferation helps a firm increase profits by satisfying various consumer needs more precisely. The third reason for product proliferation is based on strategy. Producing a number of products can not only deter entry by providing few niches, but can also cause a firm to react efficiently to a low-price entry. By producing various products, a firm can reduce niches so that potential entrants have less incentive to enter. Moreover, a firm can produce new products in response to entry, which is called fighting brands. That is, when an entrant tries to attract consumers with a low price, an incumbent introduces a new lower-quality product while maintaining the price of the existing product. The drawback of product proliferation, however, is cannibalization. Some consumers who would have bought a high-price product switch to a low-price product. Moreover, it is possible that proliferation can decrease profits when a new product is less differentiated from a rival’s than is the existing product because of more severe competition. Many studies have analyzed the effect of product line rivalry in the areas of economics and marketing. They show how a monopolist can solve the problem of cannibalization by adjusting quality in a market where consumers differ in their preferences for quality. They find that a consumer who prefers high-quality products will obtain his or her most preferred quality, but a consumer who has not such preference will obtain less than his or her preferred quality to reduce cannibalization. This study analyzed the effects of product line rivalry in a duopoly market with two types of consumers differentiated by quality preference. I assume that the two firms are asymmetric in the sense that an incumbent can produce both high- and low-quality products, while an entrant can produce only a low-quality product. The effects of product proliferation can be explained by comparing the market outcomes when an incumbent produces both products to those when it produces only one product. Compared to the case in which an incumbent produces only a high-quality product, the price of a low-quality product tends to decrease in a consumer segment that prefers low-quality products because of more severe competition. Prices, however, tend to increase in a segment with high preferences because of less severe competition. It is known that when firms compete over prices, it is optimal for a firm to increase its price when its rival increases its price, which is called a strategic complement. Since prices are strategic complements, we have two opposing effects. It turns out that the price of a high-quality product increases because the positive effect of reduced competition outweighs the negative effect of strategic complements. This implies that an incumbent needs to increase the price of a high-quality product when it is also introducing a low-quality product. However, the change in price of the entrant’s low-quality product is ambiguous. Second, compared to the case in which an incumbent produces only a low-quality product, prices tend to increase in a consumer segment with low preferences but decrease in a segment with high preferences. The prices of low-quality products decrease because the negative effect outweighs the positive effect. Moreover, when an incumbent produces both kinds of product, the price of an incumbent‘s low-quality product is higher, even though the quality of both firms’ low-quality products is the same. The reason for this is that the incumbent has less incentive to reduce the price of a low-quality product because of the negative impact on the price of its high-quality product. In fact, the effects of product line rivalry on profits depend not only on changes in price, but also on sales and cannibalization. If the difference in marginal cost is moderate compared to the difference in product quality, the positive effect of product proliferation outweighs the negative effect, thereby increasing the profit. Furthermore, if the cost difference is very large (small), an incumbent is better off producing only a low (high) quality product. Moreover, this study also analyzed the effect of product line rivalry when a firm can determine product characteristics by focusing on the issue of fighting brands. Recently, Korean air and Asiana airlines have established budget airlines called Jin air and Air Busan, respectively, to confront the launching of budget airlines such as Hansung airline and Jeju air, among others. In addition, as more online bookstores have entered the market, a leading off-line bookstore Kyobo began its own online bookstore. Through fighting brands, an incumbent with a high-quality product can increase profits by producing an additional low-quality product when its low-quality product is more differentiated from that of the entrant than is its high-quality product.

• KDI Journal of Economic Policy
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• v.12 no.2
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• pp.3-49
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• 1990

This paper analyzes U.S. demand for imports from Asian NIEs and Japan, utilizing the Almost Ideal Demand System (AIDS) developed by Deaton and Muellbauer, with an emphasis on the effect of changes in the exchange rate. The empirical model assumes a two-stage budgeting process in which the first stage represents the allocation of total U.S. demand among three groups: the Asian NIEs and Japan, six Western developed countries, and the U.S. domestic non-tradables and import competing sector. The second stage represents the allocation of total U.S. imports from the Asian NIEs and Japan among them, by country. According to the AIDS model, the share equation for the Asia NIEs and Japan in U.S. nominal GNP is estimated as a single equation for the first stage. The share equations for those five countries in total U.S. imports are estimated as a system with the general demand restrictions of homogeneity, symmetry and adding-up, together with polynomially distributed lag restrictions. The negativity condition is also satisfied for all cases. The overall results of these complicated estimations, using quarterly data from the first quarter of 1972 to the fourth quarter of 1989, are quite promising in terms of the significance of individual estimators and other statistics. The conclusions drawn from the estimation results and the derived demand elasticities can be summarized as follows: First, the exports of each Asian NIE to the U.S. are competitive with (substitutes for) Japan's exports, while complementary to the exports of fellow NIEs, with the exception of the competitive relation between Hong Kong and Singapore. Second, the exports of each Asian NIE and of Japan to the U.S. are competitive with those of Western developed countries' to the U.S, while they are complementary to the U.S.' non-tradables and import-competing sector. Third, as far as both the first and second stages of budgeting are coneidered, the imports from each Asian NIE and Japan are luxuries in total U.S. consumption. However, when only the second budgeting stage is considered, the imports from Japan and Singapore are luxuries in U.S. imports from the NIEs and Japan, while those of Korea, Taiwan and Hong Kong are necessities. Fourth, the above results may be evidenced more concretely in their implied exchange rate effects. It appears that, in general, a change in the yen-dollar exchange rate will have at least as great an impact, on an NIE's share and volume of exports to the U.S. though in the opposite direction, as a change in the exchange rate of the NIE's own currency $vis-{\grave{a}}-vis$ the dollar. Asian NIEs, therefore, should counteract yen-dollar movements in order to stabilize their exports to the U.S.. More specifically, Korea should depreciate the value of the won relative to the dollar by approximately the same proportion as the depreciation rate of the yen $vis-{\grave{a}}-vis$ the dollar, in order to maintain the volume of Korean exports to the U.S.. In the worst case scenario, Korea should devalue the won by three times the maguitude of the yen's depreciation rate, in order to keep market share in the aforementioned five countries' total exports to the U.S.. Finally, this study provides additional information which may support empirical findings on the competitive relations among the Asian NIEs and Japan. The correlation matrices among the strutures of those five countries' exports to the U.S.. during the 1970s and 1980s were estimated, with the export structure constructed as the shares of each of the 29 industrial sectors' exports as defined by the 3 digit KSIC in total exports to the U.S. from each individual country. In general, the correlation between each of the four Asian NIEs and Japan, and that between Hong Kong and Singapore, are all far below .5, while the ones among the Asian NIEs themselves (except for the one between Hong Kong and Singapore) all greatly exceed .5. If there exists a tendency on the part of the U.S. to import goods in each specific sector from different countries in a relatively constant proportion, the export structures of those countries will probably exhibit a high correlation. To take this hypothesis to the extreme, if the U.S. maintained an absolutely fixed ratio between its imports from any two countries for each of the 29 sectors, the correlation between the export structures of these two countries would be perfect. Therefore, since any two goods purchased in a fixed proportion could be classified as close complements, a high correlation between export structures will imply a complementary relationship between them. Conversely, low correlation would imply a competitive relationship. According to this interpretation, the pattern formed by the correlation coefficients among the five countries' export structures to the U.S. are consistent with the empirical findings of the regression analysis.

• Asia Marketing Journal
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• v.14 no.1
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• pp.83-98
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• 2012

In a market where new and used cars are competing with each other, we would run the risk of obtaining biased estimates of cross elasticity between them if we focus on only new cars or on only used cars. Unfortunately, most of previous studies on the automobile industry have focused on only new car models without taking into account the effect of used cars' pricing policy on new cars' market shares and vice versa, resulting in inadequate prediction of reactive pricing in response to competitors' rebate or price discount. However, there are some exceptions. Purohit (1992) and Sullivan (1990) looked into both new and used car markets at the same time to examine the effect of new car model launching on the used car prices. But their studies have some limitations in that they employed the average used car prices reported in NADA Used Car Guide instead of actual transaction prices. Some of the conflicting results may be due to this problem in the data. Park (1998) recognized this problem and used the actual prices in his study. His work is notable in that he investigated the qualitative effect of new car model launching on the pricing policy of the used car in terms of reinforcement of brand equity. The current work also used the actual price like Park (1998) but the quantitative aspect of competitive price promotion between new and used cars of the same model was explored. In this study, I develop a model that assumes that the cross elasticity between new and used cars of the same model is higher than those amongst new cars and used cars of the different model. Specifically, I apply the nested logit model that assumes the car model choice at the first stage and the choice between new and used cars at the second stage. This proposed model is compared to the IIA (Independence of Irrelevant Alternatives) model that assumes that there is no decision hierarchy but that new and used cars of the different model are all substitutable at the first stage. The data for this study are drawn from Power Information Network (PIN), an affiliate of J.D. Power and Associates. PIN collects sales transaction data from a sample of dealerships in the major metropolitan areas in the U.S. These are retail transactions, i.e., sales or leases to final consumers, excluding fleet sales and including both new car and used car sales. Each observation in the PIN database contains the transaction date, the manufacturer, model year, make, model, trim and other car information, the transaction price, consumer rebates, the interest rate, term, amount financed (when the vehicle is financed or leased), etc. I used data for the compact cars sold during the period January 2009- June 2009. The new and used cars of the top nine selling models are included in the study: Mazda 3, Honda Civic, Chevrolet Cobalt, Toyota Corolla, Hyundai Elantra, Ford Focus, Volkswagen Jetta, Nissan Sentra, and Kia Spectra. These models in the study accounted for 87% of category unit sales. Empirical application of the nested logit model showed that the proposed model outperformed the IIA (Independence of Irrelevant Alternatives) model in both calibration and holdout samples. The other comparison model that assumes choice between new and used cars at the first stage and car model choice at the second stage turned out to be mis-specfied since the dissimilarity parameter (i.e., inclusive or categroy value parameter) was estimated to be greater than 1. Post hoc analysis based on estimated parameters was conducted employing the modified Lanczo's iterative method. This method is intuitively appealing. For example, suppose a new car offers a certain amount of rebate and gains market share at first. In response to this rebate, a used car of the same model keeps decreasing price until it regains the lost market share to maintain the status quo. The new car settle down to a lowered market share due to the used car's reaction. The method enables us to find the amount of price discount to main the status quo and equilibrium market shares of the new and used cars. In the first simulation, I used Jetta as a focal brand to see how its new and used cars set prices, rebates or APR interactively assuming that reactive cars respond to price promotion to maintain the status quo. The simulation results showed that the IIA model underestimates cross elasticities, resulting in suggesting less aggressive used car price discount in response to new cars' rebate than the proposed nested logit model. In the second simulation, I used Elantra to reconfirm the result for Jetta and came to the same conclusion. In the third simulation, I had Corolla offer $1,000 rebate to see what could be the best response for Elantra's new and used cars. Interestingly, Elantra's used car could maintain the status quo by offering lower price discount ($160) than the new car ($205). In the future research, we might want to explore the plausibility of the alternative nested logit model. For example, the NUB model that assumes choice between new and used cars at the first stage and brand choice at the second stage could be a possibility even though it was rejected in the current study because of mis-specification (A dissimilarity parameter turned out to be higher than 1). The NUB model may have been rejected due to true mis-specification or data structure transmitted from a typical car dealership. In a typical car dealership, both new and used cars of the same model are displayed. Because of this fact, the BNU model that assumes brand choice at the first stage and choice between new and used cars at the second stage may have been favored in the current study since customers first choose a dealership (brand) then choose between new and used cars given this market environment. However, suppose there are dealerships that carry both new and used cars of various models, then the NUB model might fit the data as well as the BNU model. Which model is a better description of the data is an empirical question. In addition, it would be interesting to test a probabilistic mixture model of the BNU and NUB on a new data set.