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Taiwan New Orders

Price

47.096 B USD
Change +/-
-69 M USD
Percentage Change
-0.15 %

The current value of the New Orders in Taiwan is 47.096 B USD. The New Orders in Taiwan decreased to 47.096 B USD on 4/1/2024, after it was 47.165 B USD on 3/1/2024. From 1/1/1984 to 5/1/2024, the average GDP in Taiwan was 22.56 B USD. The all-time high was reached on 12/1/2021 with 67.9 B USD, while the lowest value was recorded on 2/1/1985 with 2.28 B USD.

Source: Ministry of Economic Affairs, R.O.C.

New Orders

  • 3 years

  • 5 years

  • 10 years

  • 25 Years

  • Max

New Orders

New Orders History

DateValue
4/1/202447.096 B USD
3/1/202447.165 B USD
2/1/202437.732 B USD
1/1/202448.421 B USD
12/1/202343.814 B USD
11/1/202350.627 B USD
10/1/202352.868 B USD
9/1/202351.402 B USD
8/1/202346.035 B USD
7/1/202347.728 B USD
1
2
3
4
5
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49

Similar Macro Indicators to New Orders

NameCurrentPreviousFrequency
🇹🇼
Automobile production
26,702 Units17,806 UnitsMonthly
🇹🇼
Bankruptcies
2,623 Companies2,508 CompaniesMonthly
🇹🇼
Cement production
1.076 M Tonnes727,446 TonnesMonthly
🇹🇼
Changes in Inventory Levels
6.925 B TWD-35.407 B TWDQuarter
🇹🇼
Consistency Index
92.18 points91.58 pointsMonthly
🇹🇼
Industrial production
11.22 %13.42 %Monthly
🇹🇼
Industrial Production MoM
0.54 %-0.67 %Monthly
🇹🇼
Leading Indicator
91.5 points91.3 pointsMonthly
🇹🇼
Manufacturing PMI
50.8 points51.5 pointsMonthly
🇹🇼
Manufacturing Production
16.7 %14.79 %Monthly
🇹🇼
Mining Production
-1.52 %-7.35 %Monthly
🇹🇼
Vehicle Registrations
23.161 M 23.151 M Monthly

In Taiwan, new orders significantly influence business confidence, serving as a leading indicator for growth in gross domestic product.

What is New Orders?

New Orders: A Comprehensive Analysis of Macroeconomic Significance Introduction: New orders serve as a critical barometer of economic health, providing forward-looking insights into the industrial and manufacturing sectors. Essential for both economists and investors, new orders data uncovers trends that influence market sentiments, policy-making, and fiscal strategies. At Eulerpool, our primary objective is to offer exhaustive macroeconomic data that empowers users with actionable intelligence. Within this context, the new orders category plays a pivotal role in understanding the broader economic landscape. Understanding New Orders: New orders refer to the requests placed by consumers, businesses, or governments for goods and services that are set to be manufactured or delivered in the future. This metric is typically reported monthly or quarterly by various statistical agencies and provides a leading indication of production and economic activity. Central to interpreting new orders is an appreciation of their multi-dimensional impact—it extends from supplier purchasing decisions to inventory management and ultimately to employment levels within industries. Relevance in Economic Cycles: The cyclic nature of economies means that indicators like new orders rise and fall in tandem with business cycles. During periods of economic expansion, an uptick in new orders signifies robust consumer confidence and increased business investment. Conversely, during economic contractions, declines in new orders may signal waning demand and potential production cutbacks. By closely analyzing new orders, market participants can forecast changes in GDP growth rates, business investments, and industrial production. Sector-specific Implications: A granular analysis of new orders data segmented by industry sectors provides further clarity. For instance, a surge in new orders within the technology sector may indicate imminent innovation and heightened business activities. Similarly, rising new orders in the construction industry could presage significant infrastructure projects and associated economic benefits. In manufacturing, which heavily relies on new orders data, sustained growth in orders can predict expansions in factory output and overall industrial health. Monitoring these variations enables businesses and policymakers to make informed strategic decisions. Impact on Stock Markets: New orders data holds substantial sway in financial markets. Investors closely track this metric as a proxy for corporate profitability and future earnings. For publicly traded companies, strong new orders can result in elevated stock prices, as they are generally viewed as precursors to revenue growth. Moreover, equity analysts often integrate new orders statistics into their models to refine stock ratings and investment recommendations. Consequently, timely and accurate reporting of new orders is indispensable for maintaining market efficiency. Supply Chain Dynamics: The ripple effects of new orders extend to the intricate web of supply chains. An increase in new orders necessitates higher raw material procurement and enhanced logistical coordination. Efficient supply chain management thus becomes paramount to meet delivery timelines and maintain customer satisfaction. Conversely, a downturn in new orders can lead to excess inventory, reducing operational efficiency and incurring holding costs. Analyzing new orders data helps supply chain managers optimize procurement and production schedules, aligning them with anticipated demand. Employment Correlations: The correlation between new orders and employment levels is another dimension worth exploring. Fluctuations in new orders directly affect firms' staffing decisions. In times of rising demand, businesses may ramp up hiring to scale production capabilities, thereby contributing to job creation and reduced unemployment rates. Conversely, during periods of declining new orders, firms may freeze hiring or resort to layoffs to control costs. Understanding these dynamics helps policymakers and labor economists devise appropriate employment strategies and social safety nets. Service Sector Dynamics: While often associated with the manufacturing and industrial sectors, new orders are equally relevant in the service sector. For industries like telecommunications, healthcare, and finance, new orders data can indicate burgeoning client demand for services. This metric thus informs capacity planning, resource allocation, and strategic expansions in the service sector. Tailoring new orders analysis to specific service industries provides nuanced insights, allowing firms to better align their service offerings with market needs. Global Trade Implications: In an increasingly interconnected global economy, new orders in one country can have significant repercussions worldwide. A robust increase in new orders from major economies can drive demand for exports from other countries, fostering global trade relations. Conversely, a decline in new orders can signal potential downturns in global trade volumes, affecting international suppliers and trade balances. Global market analysts and trade economists therefore closely monitor new orders data to assess and predict international trade patterns. Policy-making and Economic Planning: For governments and central banks, new orders data is a vital component of economic policy formulation. This data helps policymakers gauge economic momentum and adjust fiscal and monetary policies accordingly. For instance, a consistent rise in new orders might prompt considerations for tightening monetary policy to manage inflationary pressures. Conversely, a decline in new orders may lead to stimulus measures aimed at spurring demand. Thus, new orders data forms an indispensable tool in the arsenal of economic policymakers. Conclusion: New orders, as a macroeconomic category, offer extensive insights into numerous facets of economic activity. From guiding business investment decisions and impacting stock market trends to influencing policy-making and global trade dynamics, the importance of new orders data cannot be overstated. At Eulerpool, we are committed to providing the most comprehensive and precise macroeconomic data, enabling our users to navigate the complexities of economic landscapes with confidence. By closely analyzing and interpreting new orders data, stakeholders across the spectrum can make informed decisions that drive growth and foster economic stability.