Investing in Port Infrastructure to Lower Trade Costs in East Asia

We examine how port infrastructure affects trade and role of transport costs in driving exports and imports for East Asia. Existing studies use survey indexes to explain transport costs. These do not link investment in port infrastructure to transport costs. We include in our estimates a variable to represent the congestion of the ports to explain the transport costs. We find that the port congestion has significantly increased the transport costs from East Asia to the United States. Our analysis suggests that increase in port capacity by 10 percent could cut transport cost in East Asia by up to three percent. This translates into a 0.3 to 0.5 percent across-the-board tariff cut.


I. Introduction
This paper empirically examines how investment in port facilities affected the trade costs in East Asia. Port infrastructure has played a key role in facilitating trade in the region. However, serious congestion in seaports is evident from data on maritime shipping and trade stat, resulting in the higher trade costs in the region. The scope of the study includes the benefits of the construction of port infrastructure to address traffic congestion in East Asia.

The Important Role of Ocean Ports in the Trade of East Asia
Countries in East Asia need to rely heavily on ocean transportation as the means of international trade. Among the ASEAN5, the peninsular part of Malaysia, Singapore and Thailand are adjacent to each other, but significant amounts of the trade among them must rely on ocean transportation. Indonesia and the Philippines are islands countries. If measured by weight, virtually all the traded goods between the ASEAN5 and all of the major trading partners, the United States, Japan and China, need to move through ocean. Road and railway transports between China and some ASEAN5 members contribute to their trade, but they are limited, because major part of their international trade takes place between the industrial center of China, i.e. her coastal provinces, and ASEAN5. Air transport is rapidly increasing and taking substantial shares especially in trade value. However, the dominant value of trade of the developing countries still relies on sea transport. For example, the share of air over the total imports of Japan from China and ASEAN5 countries were only 22 percent and 26 percent, respectively, in value in 2006.
Reflecting the geographic characteristics noted above, governments in East Asia have historically set a priority on port infrastructure improvements -in coordination with an export-oriented development strategy. Transport infrastructure has also been a key sector in ODA in East Asia. Shortage in port capacity and 6 對外經濟硏究 제15권 제2호 2011년 여름호 quality in the developing countries in this region, however, has risen over the past decade.

More Congestion
The major ocean ports in East Asian developing countries have suffered from serious congestion with rapid growth in freight demand over the past decade.
Bottlenecks arise in spite of continued investments in port improvement, expansion and containerization. Figure 1 illustrates the trends in capacity and throughput in the major container ports in ASEAN5, China and Japan.  Substantial public investment in 1999 and 2000, due to the counter-cyclical fiscal policy of the Japanese government, contributed to increases in port capacity. These factors, together with substitution to air transport, have led to idol ports capacity in Japan.
Ports with sufficient capacity, efficient facilities with high technology, and good management contribute to lower costs for international transport and trade costs in total. In addition to the explicit costs from port tariffs and loading/ unloading charges, the time costs from congestion and inefficient facilities/ management contribute to transport costs. These costs are reflected in freight charges by shipping companies, storage costs, and brokerage fees by port broker incurred by traders. More frequently, these costs are charged to traders in payments to forwarders.
Our study examines whether and to what degree improvement in port infrastructure in East Asia has reduced the total costs of port transportation over the past decade. In contrast with the existing studies, which invariably estimated the effects of the port-related policies by using survey indexes on the port efficiency, our study has developed an index, explicitly measuring the congestion of the ports in East Asia. This enables us to estimate directly the effects of the investment in port infrastructure. costs. The quantity and quality of port infrastructure closely affect transport costs. Expansion of port capacity and improved port facilities can streamline and speed-up embarking and disembarking, loading and unloading process and enable to use more efficient container vessels. The time required for the port operations has been found to affect significantly the trade/transport costs. This section surveys the existing literatures on the infrastructure and transport costs, focusing on the empirical findings on the ocean ports, in particular.

Limited Availability of Trade Cost Data
The existence of trade costs is a key theoretical assumption of the standard gravity model of trade. Bilateral trade in the gravity model is determined by the 1) Defined as international trade costs divided by the value of the imported goods in the country of origin. 2) Even the lack of transparency in the trade policies would increase the trade costs because of higher risks in trade, obliging the traders to pay the premium for preventative measures in case the risks realize. See Helbel, Shepherd and Wilson (2007). and Abe and Wilson (2008 The limitation in availability of the data is also true for the narrowly-defined transport costs between the ports that constitute a part of trade costs. The authorities of most countries only publish the amounts of import on the CIF base, inclusive sum of export prices of the goods and costs for insurance and freight without showing any details. If researchers would like international transport cost data between the ports of trade partners, they must estimate the international transport cost by separating that part from the CIF import prices in most of the countries. Only the United States and New Zealand officially publish shipping/transport cost data based on the declarations from the importers for the taxation purpose. 3) Estimating trade costs for empirical analysis is challenging, therefore. An empirical compromise has been the "matching method" which uses ratio of the CIF import value divided by FOB export value between the same trading partners, whereas the former is reported from the importing country and the latter, from the exporting country. Limao and Venables (2001). estimate transport costs, or more precisely the "transport cost factors" by applying the 3) Other few countries appear to have transport data in cross-section (Hummels and Lugovskyy 2006). determinants of transport costs, which include an index of infrastructure level.
While they appear to obtain a persuasive result, the matching method should require a careful treatment in use. For instance, Hummels and Lugovskyy (2006) analyzes the accuracy of the method, comparing the estimates with the officially published import charges statistics of the United States and New Zealand, with conclusion that the matching method may generate "noisy" information.

Determinants of Transport Costs
Limao and Venables (2001) estimate determinants of transport costs, in particular those related to infrastructure. Their transport cost factor regression has distance, per capita incomes, geographical factors, such as common barriers and island dummies, and the indexes of the levels of infrastructure, including road, rail, and telephone. According to their findings, sea transport is much cheaper than land transport. In contrast, explicit measures of port infrastructure should be necessary in our study on East Asia where the dominant proportion of the trade is made between sea ports. Clark, Dollar, and Micco (2004) specifically examine the relationship between port efficiency and maritime transport costs. Instead of using the CIF/FOB matching method, they directly use the "import charges" from the United States trade statistics. The U.S. official statistics record every year the HS 6-digit commodity based, via liners, port-to-port import values, weights and "import charges", the latter roughly reflecting the transport costs between the ports 4) .
They run regression analysis for cross-section data in 1998: the dependent variable is port-to-port via-liner import charge per weight at HS 6-digit commodity level; the independent variables are bilateral (port-to-port) distance, port-to-port via-liner trade value per weight at HS 6-digit level, total import volume from the exporting country, directional imbalance in total trade between 4) According to the official source, the import charge represents the aggregate cost of all freight, insurance, and other charges (excluding U.S. import duties) incurred.
the U.S. and the exporting country, containerization ratio of the HS 6-digit based import from the exporting country, and various policy variables, as well as the efficiency indicators of sea ports of exporting countries to the ports of the U.S. 5) The authors test four different indicators as the proxies of the port efficiency, including: (i) country specific port efficiency index from The Global Competitiveness Report 6) ; (ii) total square number of largest seaports by country, normalized by the product of exporting country's population and area; (iii) GDP per capita of the exporting country; and (iv) the same infrastructure index as that used by Limao and Venables (2001). Their regression shows that all the four port efficiency indicators have significantly negative coefficients.
The improvement in port efficiency leads to reduction of the transport costs.
For other variables, the containerization ratio, directional imbalances and total liner import volume have negative coefficients, while distance and weight value have positive ones. The signs of the coefficients agree to the theoretical prediction. Blonigen and Wilson (2008) adopt an innovative methodology to estimate the efficiency of major ports in the world including the United States. Using the port-to-port, HS 6-digit commodity based import statistics of the United States, this study explored the efficiency of trading partners' ports by estimating the regression of port-to-port import charges on partner's and U.S. port-specific fixed effects, as well as a explanatory variables. Their regression has portto-port U.S. import charges in HS 6-digit commodity codes, as the dependent 5) The amounts of the trade and weight in their regression cover those transported by liners only, not include those by tankers nor tramps. They use an Instrumental Variable technique to control the endogeneity of the variable of total volume, with the instrumental variable of exporting country's GDP. 6) The Global Competitiveness Reports of the World Economic Forum publish every year the questionnaire survey results on various items related to the country's competitiveness, including the port efficiency indicators to measure the quality of infrastructure of ports and airports. The indicators reflect more or less subjective views of the respondent executives in the countries, as they are asked to respond by assigning points on the efficiency in their countries. On the other hands, the ports in Japan that are higher-ranked in efficiency generally maintain idle capacity with smaller demands. As such, the measure of port efficiency appears to strongly reflect not merely the technical efficiency, but the costs in total, including both pecuniary port tariffs and charges and the implicit time costs from the congestion and inefficiency in all the process in the ports. Moreover, the higher demand and technical efficiency may bring about rent on the port tariffs. Reflecting them, the port efficiency measurements by Blonigen and Wilson cover more than "the inherent technical efficiency of a port", reflecting other non-technical factors to determine the costs around the ports, as also observed by the authors. Our research objective calls for direct measurements to reflect the physical capacity of port infrastructure, instead of adopting their measurement. Notwithstanding, their measurements give good reference with rich information on the cost efficiency of the ports in a wider sense.

7)
For example, Singapore continues to take the top in the ranking of port infrastructure quality index in The Global Competitiveness Report.
Investing in Port Infrastructure to Lower Trade Costs in East Asia 13

Published Data on Ad valorem Transport Costs in East Asia
As noted above, U.S. official statistics report import charges aggregated at the detailed HS commodity classification.

III. Determinants of Transport Costs: Empirical Analysis
We conduct a formal regression analysis on transport costs in East Asia, using available data on transport costs, taken as import charges, of the United States. The existing studies used survey indexes to explain transport costs, failing to link the physical port investment to transport costs. Instead, we have estimated an index of physical capacity and congestion of ports, and include it in the regression as an explanatory variable in the transport cost model to measure the effects. This enables us to directly assess the infrastructure policies by domestic governments and ODAs. This section discusses the specification of the regression and the infrastructure indicators with some theoretical consideration, and examines the results.

Port-related Costs reflected in Import Charges
International transport costs between ports, defined by CIF minus FOB values, include only freight and insurance costs. But import charge statistics may cover the costs of services associated with transport: for example fees paid   The downward-sloping demand curve in the figure represents the demand for port services, 10) which is in turn derived from the demands for the imports and exports of the goods through the ports of the country. The steep slope of the curve reflects somewhat inelastic derived demand. The supply curve of the port service represents the supply price from the port authorities to the users, i.e. the port tariffs and loading/unloading charges (PT), and the cost incurred because 9) See Simeon et al. (2006). 10) The users include the shipping companies, forwarders, and ultimately the traders of the goods. Due to our additional assumption of non-existence of rents by the shipping companies, the costs for the port service fully pass through to the importers without any mark-ups.
of the congestion/inefficiency in the port (P -PT). At the time 0, the equilibrium in the market is at E 0 . With the lower full capacity of the port at F 0 before expansion of port facility, the congestion cost is larger (P 0 -PT 0 ), in spite of the smaller port tariff at PT 0 . If the port authority invests to expand the port capacity and upgrade port facilities, together with the new technology and management embodied and associated with the investment, the full capacity of the port increases to F 1 . The port tariff (horizontal) part of the supply curve may shift upward to recover the construction costs 11) , but the upward-sloping part of the supply curve, representing congestion, shifts rightward and downward. At the new equilibrium E 1 , both increase in the port tariff/charges and decrease in congestion costs take place. Only when the latter surpasses the former, this framework can consistently explain the negative coefficients of the port congestion.

Specifications and Data of the Trade Cost Regression
With the reference of the simple model illustrated above, we adopt the following specification for the regression model of the U.S. import charges per weight (equation (1)), which are similar to Clark, Dollar and Micco (2004 where: TC ikt : the amount of the import charge for the imports of the United 11) The port authority may take rent, in addition to the capital cost, due to the superior services created from the investment.

Investing in Port Infrastructure to Lower Trade Costs in East Asia 17
States via vessels from country i for commodity k at 6-digit level, at the year t.
distit: bilateral distance between country i and the United States. The distance is calculated as the weighted average of the port-to-port liner distances between major ports in country i and Seattle, Los Angeles and New York, using the actual flows of container cargos in 1998 and 2003 as the weight (Shibasaki et al. 2004 12) ). The  2) t-values in parentheses. *** significant at 1% , ** at 5%, * at 10%.  change in the indexes. Because of the lack of data on Viet Nam, the third specification uses fewer observations.
The first specification that uses our port congestion index results in the values of parameters on distance, value/weight, weight, and containerization ratio, which are generally within the comparable range to the existing empirical studies. The distance variable has an elasticity, with a value of positive but less than one, as a standard gravity equation expects. The estimated elasticity of the value/weight variable has a positive value, as luxurious commodities require more transport costs. The weight variable has a negative elasticity, as bulky 20 對外經濟硏究 제15권 제2호 2011년 여름호 commodities tend to be transported cheaply.
Our port congestion index takes a significantly positive coefficient. This is the expected result by our partial equilibrium framework, illustrated in Figure   2 above. The estimated value implies that the expansion of port capacity by 19 percent in China, which is the annual average growth rate of the estimated port capacity from 2001 to 2006, would ceteris paribus reduce the international transport cost, measured by import charge, by 2 percent. 14) The other two indicators of port performance reflect opinion survey results. The

14)
We have tested the fixed and random effects methods by adding to the regression i times k dyad dummies to control the pair relation between the exporting country and commodity. A robust result has emerged, both from the fixed and random effects, with the statistically significant estimates of coefficients of the port congestion index at around 0.05 to 0.06. This result would support the credibility of the significance of the port congestion index.

Investing in Port Infrastructure to Lower Trade Costs in East Asia 21
The three indicators on ports used above should reflect information overlapping each other. Table 3 shows the correlations between the three indicators and the port efficiency measures by Blonigen and Wilson (2008)  Our port congestion index partially correlates to the port efficiency measurement by Blonigen and Wilson. No significant correlation, however, is found with the indexes from GCR and WCY. Our port congestion index represents narrowly-defined physical congestion/utilization of ports and possibly some rents from the higher demands and technical efficiency. The other two indexes reflect survey opinions that reflect a much wider scope and perceptions.
Our index does correlate to the port efficiency index by Blonigen and Wilson which is supposed to cover all port-related costs incurred by transporters, because it is the value of the port-specific fixed effects. The indexes from GCR and WCY also correlate to the port efficiency index, showing that both of the indexes also contain information on the costs on ports.

If the port efficiency measurement of Blonigen and Wilson is regressed on
15) The journal article only puts a table showing a measurement averaged throughout the years from 1991 to 2003 on each foreign port. We take simple averages of ports in a country to obtain the index of the country, and assume the port efficiency measurements do not change over time from 2001 to 2006 to calculate the correlations in Table 3. our port congestion index, time dummies and constant, the estimated coefficient of our index is 0.049, significant at the 1 percent level. The regression can explain around 15 percent of the total sum of the squares. For the same example above, the expansion of port capacity by 18 percent for China in 2006 will brings about the fall in the port efficiency measurement by 1.3 percent.
Because the port efficiency index is measured in terms of fixed effects in the regression of import charges, its fall by 1.3 percent just means the fall in import charges by the same percentage. The estimated results regression (1) implies that the same shock will bring about the fall in import charge by 2 percent. These comparable results from the two difference approaches reinforce the plausibility of our estimates.

IV. Benefits of Port Infrastructure Improvement in
East Asia

What are the benefits from the Port Construction?
With a considerable surge in demand for exports and imports, port authorities in the developing countries in East Asia rapidly expanded the capacity of their container ports in the 2000s. However, serious congestion remains. Our regression analysis suggests that the expansion of port infrastructure would ceteris paribus reduce the import charges/trade costs, ultimately paid by the importers. In turn, reduction in the transport costs may lead to an expansion of trade through the ports. The consumer surplus for the importers should increase.
The partial equilibrium framework illustrated in Figure 2 above helps consider what happens to the welfare of the port users. In the diagram, the increase in welfare to the users, i.e. the consumer surplus, is brought about by the decline of the port-related total transport cost from P 0 to P 1 and the benefit from the reduction of congestion. The decline in the costs for port services is This correspond to a rectangular, instead of trapezium P 0 P 1 E 1 E 0 , ignoring the small remaining triangle, giving an acceptable approximation. One should note that the consumer surplus in the framework, as well as the estimated gains in the consumer surplus, is affected by the costs caused by the congestion and port tariffs and other charges. 17)

The Baseline Policy Scenario and its Impacts on Transport Cost
We set a policy scenario on the expansion of the capacity of the major ports in the developing countries in East Asia. Table 4 below shows the impacts on the transport costs for the import of the countries under our baseline scenario.
Our policy scenario is such that the port capacity in the developing countries in East Asia is invariably expanded by 10 percent.
16) However, we may obtain a rough idea of the consumer surplus, if we assume some plausible number as Ad valorem tax-equivalent transport costs on import prices, for example, at 30 percent. 17) The shipping companies and forwarders are assumed to pass on all the costs in ports to the importers, which are recorded as the import charges in the official statistics.  (2) Where f(…) and g(…) represent functions, taking the explanatory variables in regression (1), except for the PIndex. Subscripts i and j denote the exporting and importing countries.
The specification (2) generalizes the stipulation of (1) by including the costs incurred to the traders both in exporting and importing ports (i.e. variables Investing in Port Infrastructure to Lower Trade Costs in East Asia 25 portcost i and portcost j , or PIndex i and PIndex j , more specifically). We have added somewhat bold assumption that γ 1 and γ 2 take the same value that is equal to what is estimated in regression (1). The numbers in the second column represent the impacts on the transport costs for import of the countries in terms of the percentage change, consisting of the cost-reducing effects in both from (i) their own ports for unloading (the third column) and (ii) the ports of their trade partners for loading (forth column).
The estimated reduction in the transport costs of imports ranges from one half to nearly three percent. The impact is significant. For example, one may recall that the leaders of Asia-Pacific Economic Cooperation in 2001 committed to implementing the APEC Trade Facilitation Principles (Shanghai Accord) with a view to reducing trade transaction cost by five percent by 2006 18) . The transaction cost defined in the Accord covers the wider scope of trade cost than the narrowly-defined international transport cost, but the latter represents a significant proportion of the former, around one third 19) . The estimated impacts of the Baseline Scenario would enable several APEC members to meet even one sixth of the target of the Accord .
Moreover, if we assume that the international transport costs are 20 percent Ad valorem tax-equivalent on import prices for all the countries, the cost reduction effect is from 0.3 to 0.5 percent of the import prices among the developing economies in East Asia. The assumption of 20 percent above is at the modest side, as the transport cost for the U.S. imports are estimated to be for the developing countries is certainly higher. This cost reduction effect in the Ad valorem terms is equivalent to the across-the-board tariff reduction of the same percentage, covering all the imported commodities. As the Baseline Scenario can be realistically achieved, port investment provides an effective tool for trade facilitation.

V. Implications
The analysis in this paper suggests the following conclusions. First, port congestion in East Asian countries has significantly increased their transport costs. An increase in exports played an important role for these economies to achieve the post-crisis recovery in the 1990s, however infrastructure bottlenecks must have posed a serious obstacle to recovery in 2000s.
Second, the expansion of the port capacity under our baseline scenario, which is rather modest, to expand the port physical capacity by 10 percent suggests that transport costs in East Asia could decline by one-half to three percent. If transport costs constitute about 20 percent Ad valorem tax-equivalent on the import price, the effect is about a 0.3 to 0.5 percent across-the-board cut in tariffs.
We may draw two implications from the analysis. First, port infrastructure improvement could provide very good opportunity for trade liberalization and facilitation for the region. In particular, the economies of Singapore and Hong Kong, where tariff rates are virtually zero, will be able to proceed with further trade liberalization and facilitation by expanding and improving their port facilities. Second, the nature of the effect of port infrastructure improvements is equivalent to across-the-board uniform tariff reductions. As such, importing countries would suffer less from trade diversion and port investment may face less serious resistance in a public policy context. Appendix 1: Construction of Port Congestion Index The index to compile is aimed to examining the effect of the physical investment of the ocean container-specialized port facilities on the trade costs.
As stipulated in the fourth section in the main text, the capacity of the port directly affects the costs for its services in two aspects: the first is through the port tariffs and other charges for the unloading and loading services, and the second is the time costs due to the congestion. The expansion of the port capacity is accompanied by higher tariffs and charges, but lower degrees of congestion and waiting time for the movement of goods.
We have compiled an index of port turnover, defined as the sum of the loaded and unloaded containers in TEU (Twenty-foot Equivalent Unit) at the major container ports in the country i in the year t, divided by the sum of the estimated capacity of the major container ports in the country i in the year t.
Table below summarizes the ports referred to in the compilation of the index, together with the actual throughput and estimated port capacity of each port, and estimated port congestion turnover index for the country/economy. The numerator of the congestion index reflects the actual throughput of the major ports reported in the issues of Containerization Yearbook. The same reference is used to estimate the capacity.
The estimate of the port capacity builds on only the physical magnitude. The capacity is in terms of TEU units that can be physically accommodated at a port at any one point in time. The number is determined by the number and length of berth and their depth. We put the following assumption on the full physical capacity of the port, based on the numbers and depths of the berths: The berths with 14 meters or deeper in depth can accommodate the vessel with 6000 TEU. A vessel uses up 250 meters of the berth. The births with 13 meters in depth can accommodate the vessels with 3250 TEU, using up 200 meters of the berth. Those with 12 meters in depth, the vessels with 1750 TEU, using up 150 meters of berth. Those with less than 10 meters in depth, 500 TEU, using 100 meters and less of berth. Combination of various sizes of vessels are applied to maximize the estimated capacity the port can accommodate at once.
The index is in terms of ratio. The higher the ratio is, the more the costs of congestion are, and the more changes to force the traders the waste of time.
The index builds on the major ports in East Asia, which conduct most of the international trade. In this sense, this index should not be regarded as proxy.