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Lund University

Economics: Time Series Analysis

<p>In econometrics, data is either cross-sectional (e.g. different individuals or countries) or time series (development over time). In this course, you will devote yourself to the analysis of data that are time stamped and the specialised econometric tools needed to analyse time series data.</p><p>Time series data…

  • Higher education
  • Information unavailable
  • 18 January 2027
  • Lund
  • Information unavailable
  • 50 %

Overview

<p>In econometrics, data is either cross-sectional (e.g. different individuals or countries) or time series (development over time). In this course, you will devote yourself to the analysis of data that are time stamped and the specialised econometric tools needed to analyse time series data.</p><p>Time series data occur in a sequence and represent different points in time. Thus, we can plot time series data in a figure. For a trained eye, such time series plots can be extremely informative. In fact, just looking at a time series plot ("eyeball econometrics") is often enough to determine the most appropriate econometric approach. Because of this, the course is organised based on how data look. </p><p>A key distinction is whether the data tend to move around a mean value or if it have a long term upward or downward trend. Some time series, like GDP or unemployment growth, never wander far away from their mean. Other time series are trending. Examples include prices, income, exchange rates and consumption. If a time series is trending, you need different methods to analyse compared to when it is not. </p><p>Thus, to identify the most appropriate approach, you need to take the look and length of a time series into account. In this course, you will learn how to do this. You will developing an in-depth understanding for what works and what doesn’t based on theoretical knowledge and hands-on experience with a range of approaches. This will leave you with a pallet of tools that can be selectively deployed depending on how the data look. And if you find yourself in uncharted territory, the focus we place on in-depth understanding will help you find a solution.</p><p> </p>

Admission scores

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Entry requirements

Students admitted to the Master Programme in Economics or the Master Program in Finance, and who have taken the courses NEKN31 “Advanced Econometrics” or NEKN82 “Empirical Finance”, are eligible to take this course. Students admitted to the Master Programme in Data Analytics and Business Economics are eligible to take this course. For other students at least 90 ECTS-credits in economics are required. These must include 15 ECTS-credits at the advanced level, including the course NEKN31 "Advanced Econometrics" or NEKN82 “Empirical Finance” or an equivalent course in econometrics at the advanced level.

The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.

Source, measure and data quality
Source
Skolverket Susa-navet
Period
2027-01-18
Measure
Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
Population
Education offering e.uoh.lu.nekn34.61652.20271
Last checked
2026-09-23T10:38:33.477975+00:00
Limitation
Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.

Programme content

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Study structure

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  2. Programme or course ends

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About the provider

Lund University

Provider for the published education offering.

Sources and data quality

Education facts for the selected offering come from Skolverket Susa-navet.

Retrieved . Published . Times are shown in Swedish local time.

Source identity and publication version
Publication version
8e217193-f5fa-4778-b085-a4521fd03e8d
Education identity in the source
i.uoh.lu.nekn34.61652.20271
Offering identity in the source
e.uoh.lu.nekn34.61652.20271
Education-form source code
HS
Education code in the source
NEKN34
Change time according to the source
2026-07-06T16:59:14

The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.