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🐦✨ Exciting news, #Gretl users! The latest issue of Computational Statistics is out, featuring 5 articles on our favorite opensource econometrics & statistics software! 🎉📊

These articles explore advanced modeling techniques such as
- Bayesian VARs
- Time-varying parameter model

It's fantastic to see Gretl gaining recognition in the academic community!

Check out the full issue here:
link.springer.com/journal/180/

⚡#China's July youth unemployment rate(16-24yo, students excluded) was 17.1%, vs 13.2% in June, the highest since ever record from January. NBS explained that the high youth jobless rate is affected by the graduation season. #Econtwitter #ChinaChart
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This wasn't a summary. Read the whole paper here for free: doi.org/10.1007/s11233-024-091. #EconTwitter #HigherEd #AcademicChatter (8/9)

SpringerLinkThe cross-employment of PhDs across the university sector boundary: an analysis of Finnish register data - Tertiary Education and ManagementTacit knowledge flows can be facilitated by employment transitions, such as for example the transitions of PhDs from university employment to industry. There are however barriers to transitions into and out of university employment, and as a consequence, such transitions are relatively rare. PhDs can circumvent the barriers to permanent transitions by simultaneous secondary employment relationships. Though we know that such cross-employment exists, we do not know how common it de facto is. In this paper, we use a nine-year panel of daily-level employment microdata on the full population of Finnish PhDs to show that about 30% of university-employed PhDs are cross-employed outside of universities. This is a substantial share, and its magnitude alone suggests a central but underappreciated role for cross-employment in contemporary knowledge production and dissemination. We furthermore find that similar numbers of non–university-employed PhDs are cross-employed at universities as university PhDs are cross-employed outside of universities, and that many cross-employment relationships are in non-technical fields, and with public sector organizations. This illustrates the importance of understanding the nature of knowledge flows other than the unidirectional flows of technical knowledge from universities to industrial firms.

"#Fintech" is a fraudulent marketing term. There's nothing Buy Now Pay Later companies offer that couldn't have been done 100 years ago. They just replace interest with penalties for late payment.

Upton Sinclair described a similar racket in The Jungle (set in 1920s, I think). Home loans with no money down and low interest, but if you miss a single payment you lose everything.

I've been making this point a lot recently, thinking it was original, but @delong posted it more than a year ago. The accelerationist model of inflation from which the NAIRU is derived works only for the 1970s.

Earlier inflations in the 1950s, and the current #inflation don't fit the model at all well, in either US or Australia.

Pre-NAIRU Keynesian understanding of the Phillips curve saw strong aggregate demand as driving both lower unemployment and higher inflation.
In #NAIRU model, transmission mechanism is from (low) unemployment to wages to prices.

open.substack.com/pub/braddelo

Brad DeLong's Grasping Reality · HOISTED FROM ÞE ARCHIVES: Six Episodes of U.S. Inflation Above 5%/Year in þe 1900sBy Brad DeLong

Trying myself on unknown terrain: Just published a working paper about the use of Large Language Models for low-resource programming languages! 🖥️👋

The study shows that #LLM-s can be a useful for writing, understanding, improving and documenting code.

I choose #gretl + its domain-specific scripting language for #statistics + #econometrics for illustration.

Comments welcome!
arxiv.org/abs/2307.13018

#softwaredevelopment #computerscience #GPT3.5 #econtwitter

@gretl

arXiv.orgThe potential of LLMs for coding with low-resource and domain-specific programming languagesThis paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.