Assignment Task:
Task:
Many macroeconomic data series, including Gross Domestic Product (GDP), are published with a lag. The problem of data lag is partially mitigated by the use of more regular activity-based indicators such as the monthly industrial production and retail sales indices. Such indicators are further complemented by survey-based sentiment indices¹ which measure economic agents’ perception of the outlook of the economy in the near future. In this study, we tap on unconventional data sources to obtain a higher-frequency and more real-time measure of economic sentiments in Singapore. This is part of our effort to expand the use of high frequency, real-time data to complement traditional indicators for better monitoring of the health of the Singapore economy.² Role of economic sentiments in understanding the health of the economy Economic sentiments play a role in influencing economic outcomes (Throop, 1992). For example, the level of optimism in the economy can affect consumers’ saving and spending activities, business owners’ hiring and capital expenditure plans, and the amount of credits available to businesses. Both activitybased indicators and economic sentiments are thus important barometers for assessing the overall health of the economy and can offer new insights to policymakers (Exhibit 1). For instance, when both economic sentiments and activity-based indicators are positive (negative), they may reinforce each other to increase the likelihood of an improving (deteriorating) economy. On the other hand, mixed signals could suggest that the economy is at a turning point.
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Get Help Now!Measuring economic sentiments in Singapore using non-survey based information
As far as we are aware, almost all sentiment-based indices in Singapore rely on purpose-built surveys to gather the sentiments of consumers or businesses. However, another possible source of data on economic sentiments is the news media. This is particularly since the news media is the primary source of information on the latest economic events and developments for many economic agents (i.e., consumers and businesses). The tone used in economic reporting thus not only reflects current sentiments, but could also prompt the economic agents to revise their sentiments. Increasingly, text analytics techniques have been used overseas to mine sentiments from the news media. For example, studies overseas have focused on using text-derived sentiments to predict stock market movements (Schumaker & Chen, 2009; Garcia, 2013), labour market outcomes (Levenberg, Pulman, Moilanen & Simpson, 2014) and economic growth (Ormerod, Nyman & Tuckett, 2015). Here, we construct the Singapore News Economic Sentiment Index (SNES) to measure economic sentiments as portrayed by the local newspapers, and also assess the extent to which it correlates with the performance of the Singapore economy. To construct the SNES, economic-related articles published in the local newspapers³ between January 2001 and June 2016 were first identified.4 In total, more than 217,300 economic-related articles were identified for the construction of the SNES.
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