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Trade uncertainty does influence the firm’s new investment, profitability and supply chain finance. Consequently, it results in decreased consumption and low consumer confidence and eventually disrupts global economic activity. This paper aims to propose a model to uncover the effects of trade policy uncertainty (TPU) on the real economic activity and economy’s health measured in terms of the purchasing manager’s index (PMI).

This study uses the PMI, trade policy uncertainty index, economic policy uncertainty index and short-term interest rate. The relation between economic activity and uncertainty was studied using nested regression and vector autoregressive model.

The empirical results show that PMI of China and Japan were more responsive to the TPU of the USA and remained more fluctuating during the year 2018–2019. Importantly, this paper notices that the US’s PMI reached a low historically subject to its own trade policy and tension with China. Overall, TPU has shown more pronounced effects on PMI across China, Japan and the USA, followed by important economic and political events and major trade tariff uncertainty deals.

The empirical outcome holds some practical implications trade uncertainty affects not only the economic health of the economy but also market participants, global investors and international political environment, recent trade barriers, tariff wars and ambiguity raise question about free and fair global trade and competitiveness of the member country of the world trade organization.

The work is a novel that attempts to explain economic activity and supply chain through PMI. Unlike conventional economic indicators, e.g. gross domestic product, producer price index, consumer price index, employment, etc. PMI measures manufacturing industries’ overall status concerning the number of orders, inventory levels, productions, supplier deliveries and employment.

The purpose of this study is to determine which quantitative metrics are most representative of investor sentiment in the US equity markets. Sentiment is the aggregation of consumers', investors', and producers' thoughts and opinions about the future of the financial markets. By analyzing the change in popular economic indicators, financial market statistics, and sentiment reports, we can gain information on investor reactions. Furthermore, we will use machine learning techniques to develop predictive models that will attempt to forecast whether the stock market will go up or down based on the percent change in these indicators.

In the maritime industry, it is vital to have a reliable forecast of container shipping demand. Although indicators of economic conditions have been used in modeling container shipping demand on major routes such as those from East Asia to the USA, the duration of such indicators’ effects on container movement demand have not been systematically examined. To bridge this gap in research, this study aims to identify the important US economic indicators that significantly affect the volume of container movements and empirically reveal the duration of such impacts.

The durability of economic indicators on container movements is identified by a vector autoregression (VAR) model using monthly-based time-series data. In the VAR model, this paper can analyze the effect of economic indicators at t-k on container movement at time t. In the model, this paper considers nine US economic indicators as explanatory variables that are likely to affect container movements. Time-series data are used for 228 months from January 2001 to December 2019.

In the mainland China route, “building permission” receives high impact and has a duration of 14 months, reflecting the fact that China exports a high volume of housing-related goods to the USA. Regarding the South Korea and Japan routes, where high volumes of machinery goods are exported to the USA, the “index of industrial production” receives a high impact with 11 and 13 months’ duration, respectively. On the Taiwan route, as several types of goods are transported with significant shares, “building permits” and “index of industrial production” have important effects.

Freight demand forecasting for bulk cargo is a popular research field because of the public availability of several time-series data. However, no study to date has measured the impact and durability of economic indicators on container movement. To bridge the gap in the literature in terms of the impact of economic indicators and their durability, this paper developed a time-series model of the container movement from East Asia to the USA.

Since the transportation sector plays an important role in the initiation and propagation of business cycles, in previous chapters we developed output [transportation services output (TSI)] and other indicators to construct an index of coincident indicators for the U.S. transportation sector to identify its current state. We defined the reference cycle, including both business and growth cycles for this sector beginning in 1979 using both the conventional National Bureau of Economic Research (NBER) method and modern time series models. A one-to-one correspondence between cycles in the transportation sector and those in the aggregate economy was found; however, both business and growth cycles of transportation often start earlier and end later than those of the overall economy. Although the knowledge and inference based on coincident indicators can serve as an important reference for planning and other decision-making processes, these indicators are also subject to substantial lag due to data collection, processing and revision, underscoring the need to develop a system of leading indicators for the industry. Thus, in this chapter, we construct an index of leading indicators for the transportation sector as a forecasting tool using rigorous statistical procedures.

Japan has always been an “odd man out” from the standpoint of Western norm or Western finance. It is a country that is as developed as any in the West. However, it is also a country that possesses the significant institutional and cultural traits that separate it from the West. An important question in finance is to what extent the basic models of finance, developed with the Western “perfect market” view in mind, can be applied to Japan; or conversely, what critical adjustments must be made to make models amenable to the reality of Japanese finance.