Notice that the pricing will come down. In Germany (where the market is mature), I can buy a 2kWp system for 500-600 EUR. Then your payback time basically halves...
as just confirmed in the press conference, the overall liquidity safety net is actually 200B CHF from SNB. Then 9B of guarantees from the Swiss government to UBS for potential risks
Additionally there are preparations to temporarily suspend noise/pollution legislation that forbids backup power generators to run for more than 50 hours a year [0]. While the current idea is to only exempt sites (around 300 sites, 250 MW installed capacity) that are already used by SwissGrid for Ancillary Services [1], there is political pressure to temporarily include all sites with installed backup power generators (> 4 GW).
If even a fraction of this installed capacity would run in times of shortages, this should further reduce demand without causing disruption on industrial production or even having to schedule rolling blackouts.
Nitpicking: Switzerland actually does have three ports that provide, protected by international law, access to the North Sea (via the Rhine) and the Black Sea (via the Rhine–Main–Danube canal). In terms of quantities, about 10% of imports are going through these ports, mainly bulk load.
This is actually a main proposal by William Nordhaus [1], who won the Nobel Memorial Prize in Economics on climate change modelling! TLDR: So called climate clubs (or "reasonable countries") would punish countries that are not meeting the clubs rules (i.e. a carbon tax of a certain level) by levying tariffs.
And I pay 0 swiss francs for an account + card (you need more than 25k of assets, else its 5...But any product such as third pillar retirement funds count!) with unlimited transactions and cash-withdrawal at any ATM. You probably have to shop around.
The reason why banks are charging now for simple accounts, is that since we have negative interest rates (the lowest in the world), its actually damn difficult for banks to make a profit now with normal accounts since the traditional business model of the difference in interest rates is now actually reversed (the target rate is negative, yet on my account I have 0%...).
I would also have a look at Hasura GraphQLEngine. Have used it now for various projects and is extremely nice, especially with the superb subscriptions support and eventing for the odd requirement that cant be handled within Postgres
Just a quick one: why would you need redux for forms? This is in my opinion a total overkill.
I have forms either having their own state or (preferred) just use Formik for all of this. In my stack, this then allows to just add a field in the GraphQL schema (backend), add it in the query, add the formik field + yup validation and done.
I can not really give you an intuitive explanation, but economists usually refer to bubbles (or disequilibrium), when actual asset prices deviate from the prices estimated based on the identified long term equilibrium properties of often co-integrated variables.
To identify such models, VAR and SVAR (Structural Vector Autoregressive) analysis are often used, where up to 15-20 time series fed into. Such approaches of course come with their sets of necessary assumptions, but wich are in the case of VAR in levels quite reasonable...
Basically the assumption behind such kind of analysis is, that in the long run, there is some kind of equilibrium path were forces of nature/system are pushing towards to, but to identify disequilibria, you need to look at the whole system and not only 1 or two (as a ratio) variables.
An interesting application about identifying "bubbles" in housing prices with VAR you can find here [1].
From economic theory, the concept of time inconsistency [1] in my opinion explains pretty well whats currently going on:
For current governments, it is allegedly optimal to not take immediate action but to announce/commit to actions in the future. Problem is, that for the next government, the same result from the optimization problem arises.
A similar pattern can be found with nuclear waste, a problem that is known since many decades, yet there are very few permanent solutions.
Well, I don't want to be pedantic, but don't you rather mean "Most TSA MODELS require data to be stationary"? My experience has been, that often practical TSA actually involves how to deal (testing, differencing, smoothing...) with non-stationarity, which is often not a trivial task...
A year ago, the original blog post [1] (it was just recently updated, which is now the one linked here on HN) helped me on a semester thesis, where I quite successfully used LSTM for short-term electricity load forecasting, which also has very strong daily, weekly and seasonal patterns. I used multiple features/variables such as calendar and weather data and found the LSTM models to easily beat ARIMA/TBATS forecasts.
You can find the code repo on my Github link [2], but please bear with the code quality. I only have an economics background, so my coding experience is fairly limited :)