Are We Tired of Saving The Planet?

Sales of fuel efficient cars in the Netherlands went drastically up for a short period between 2008 and 2013. A-labelled cars, or the most efficient ones, jumped from 5% to above 60% in the period of 7 years. With increasing fuel efficiency and every new generation of cars being cleaner, new standards were needed. The Dutch relative system of energy labelling ensures that fuel efficiency of a car is compared to that of all cars with the same size. From 2014, more fuel non-efficient cars are being registered every year. As fuel efficiency is increasing and the average CO2, emission is falling, it is becoming more difficult for all new registered cars to fall under the A or B label. This piece is going to look at the forces at work of fuel economy labelling from 2005 until today.

Fuel inefficient cars have become quite popular in The Netherlands during the past four years. Did we just give up on our fight for the environment? Do we care more about the size of our cars? Have taxes on fuel efficiency not helped at all?

Let’s go back in time: In 1999, in an effort to push the environmental agenda further, the EU expanded the labelling of energy-consuming products to passenger cars. Two years later, the fuel energy labelling of cars was introduced in the Netherlands.

How does the labelling work? The new taxonomy grouped the relationship between distance travelled and the amount of fuel consumed by a vehicle in seven categories (A to G). A-labelled cars were the most fuel efficient as they emit the least amount of CO2 per kilometre travelled, while G-type of cars were the last.

However, every member state has autonomy in its exact labelling. The Dutch system of energy labels is one relative system: the label indicates whether a car within its segment is economical or not and it also indicates how economical a car is compared to other cars that are about the same size.

Initially, the range of cars with an A-label was initially small: only 1% or 2% of the car models had an A-label. The share of B-labels varied between 5 and 10%. Since 2008, the range of car models with an A or B label grew rapidly until 2013 and this happened for mainly two reasons.

Firstly, due to the strong influence from the EU with respect to standards for CO2 emissions, car manufacturers supplied more and more fuel-efficient cars in the market.

Secondly, the calculation rules used to determine the energy labels in the Netherlands were relaxed between 2008 and 2013, making car models A and B more available and attractive for buyers.

With the expansion in the shares of A and B labelled cars, a more balanced spreading of energy labels was created. The market share of cars with relatively inefficient labels of D through G fell drastically between 2008 and 2013. The market for environmentally cars was booming, but only for a short while.

What happened?

Technology is helping. Every new generation of cars is more economical and cleaner. By 2013, more than 60% of the cars registered were of type A.

The energy label, however, indicates the economy of a car, compared to the average economy in the whole class. As the cars with the latest technologies are emitting less and less, the average fuel efficiency has improved every year. If there are better performing cars in the basket of the best performing ones, they should be classified differently.

The boost in fuel efficiency required new thresholds for the classification. Until 2013, a car had to be more than 20% more efficient than average to qualify for an A-label, but at the beginning of 2013 that limit has been reduced to 15%.

For the 2014 and 2015 labels, the calculation was done using the average emission applied from sales in the years 2011 and 2012.

Because in the period 2008-2013 the average CO2 emissions per vehicle kilometre of newly sold passenger cars decreased by an average of 7% annually (Dutch Government, 2017), the updating of the reference period is the CO2 reference standard tightened considerably.

This led to the supply of cars with an A or B-label falling in 2014. In 2015, this supply went up again at the level of 2011 and 2012. For the labels of 2016 and 2017, the average emission of the sales in the years 2013 and 2014 was applied. As a result, the CO2 reference standard has been tightened up again and the supply of cars with an A or B label fell.

Not surprisingly, average CO2/km emissions decreased in all countries in 2016, except in the Netherlands, where emissions increased by almost 5% to 106 g CO2/km. (European Environment Agency, 2017)

Data and Insights

Since 2005 until last month, there are on average 465 thousand new cars registered each year in the Netherlands, or around 40 thousand new cars each month.

More new cars are being registered today than there were in the past. In 2017 there were around 575 thousand cars registered, 60 thousand more than in 2016. The impact of the financial crisis is visible in 2009 when sales dropped by 17%.

Figure 1: Cars registered in Holland every year since 2005

Cars Figure 1.jpgNow, the market is growing. Even though we are a bit more than half way through 2018, car sales this year are higher than the post-crisis year of 2009.

Figure 1 shows the exact number of cars being registered by fuel energy label each year. Even in nominal terms, the sharp rise of A-labelled and B-labelled cars during 2008-2013 is obvious. So is the downturn of these numbers in 2014, when the market was shared much more evenly. A higher supply accompanied by higher tax benefits for these type of cars are the main drivers behind this increase.

Figure 2 below shows the percentage of labels A to G from 2005 until 2018. The most fuel efficient new cars (labels A and B) covered around 24% of all cars in 2005 and in 2013 these two labels had the biggest piece of the cake, at around 82%.

Figure 2: Percentage of cars registered in Holland every year since 2005 by fuel energy ratiCars Figure 2.jpg

The basket of inefficient cars also changed in size as the percentage for these labels has increased. For example, for the G-label, up to 2013 a car should have been at least 30% less efficient than average. Since then, it has changed to at least 35%.

Let’s take it further: Let’s make the assumption that D-labelled cars are the cut-off point of fuel efficiency. What happened to the number of cars labelled D to G and most importantly did it grow in relative size?

Figure 3: Number of cars with energy label D-G registered in Holland every year since 2005

Cars Figure 3

Figure 3 shows that, by 2017, the Dutch were buying four times more fuel inefficient cars than they were buying in 2013. However, this does not necessarily mean that there are in total more inefficient cars today than there were in 2013. It means that the average level of fuel efficiency is increasing and label calculations are becoming stricter for the most efficient categories.

In a publication back in the 2014, TNO suggested that in the Netherlands a large number of people drive company cars and it is considered as a job benefit with a limited income tax burden. That means that companies, which are the owners of these cars have little tax incentive to buy fuel efficient cars. Their employees can enjoy their ride to work with comfortable and relatively more polluting cars as the tax burden is so small. It could be one of the drivers why the environmental ogres are increasing.

Figure 4: Percentage of cars with energy label D-G registered in Holland every year since 2005.

Cars Figure 4.jpg

There has also been a noticeable increase of the percentage of “environmental ogres” relative to the size of all cars registered. While, only 6% of cars registered in 2013 was labelled D through G, four years later this increased to 22%.

However, labelling is relative. The picture will definitely change in the coming years. As almost all manufacturers are producing environmental friendly cars, the average emission per car is being pushed down. In two years, labelling will depend on the sales now and the level of emissions now.

If there are again a lot of fuel inefficient cars, the government might relax the labelling calculations accordingly to push more people to buy fuel efficient cars.

Due to the environmental benefits of lower fuel consumption, the Dutch government has been encouraging the purchase of fuel-efficient cars through tax benefits. In turn, this pushed the sales of fuel efficient cars up, but only for a short while.

However, in the Netherlands the labelling of fuel energy is relative: a car could be A-labelled only if it is at least 20% more efficient. As the average level of CO2 emissions went down, the new threshold dropped to 15%. This explains why the share of non-efficient cars went up since 2013.

Lastly, we did not stop caring about the environment, especially after the attractive tax incentives that the government is imposing. It is just becoming more difficult to show that we care more than others.

Download the full report: Are We Tired of Saving The Planet?

Is Compulsive Flying Disorder a Thing?

People are flying a lot more than they used to. The growth in demand has been triggered from lower fare prices, higher disposable incomes, the growth of middle-class and countless new routes. According to the International Air Transport Association (IATA), 2017 was another year of above-trend passenger growth, well ahead of the ten-year average pace of 5.5% and faster than that of capacity. By 2035 around 8 billion passengers are expected to travel by plane each year, double the amount of present levels. This report will look at passenger traffic in the Dutch air hub (Schiphol) during the past twenty years and discuss the difference in seasonal peaks between passengers  travelling to world-wide destinations  and passengers travelling to European destinations.

Taking a flight is a lot cheaper, easier and more popular than it was twenty years ago. Searching for a ticket online has never been easier as ticket platforms are booming. In Europe, flying abroad for a weekend to visit a friend or a relative, or just to explore a new city has become possible for everyone.

In relative terms, a passenger with median income is able to afford more flights per  year today than he could twenty years ago, as his disposable income has surged along and relative costs have fallen. There are numerous reasons why travelling has become more affordable.

As technology advances at an exceeding speed, the costs of flying a plane have decreased and the overall efficiency of a single flight has increased. The short-run outcome is noticeable as technology has decreased the cost per ticket and increased demand.

There has been less pressure from the oil market as crude oil prices have relatively fallen. The price of oil counts for a vast share of the cost of an airline. As oil prices have relatively fallen, the prices of airfares have followed.

Additionally, flying is not considered a luxurious service anymore, but rather one that is reachable to everyone.  Airlines have increased the number of seats per aircraft and have decreased legroom per seat.  On average, legroom and seat width has decreased from 5cm to 10cm in the past 30 years and more people are being packed in the same space. (Telegraph, 2018)

On top of that, extra services from baggage handling to a glass of water on board have an additional cost for short flights. That means that if you have a carry-on and hopefully do not get thirsty, you can often get a great deal for a flight.

The increase in flight demand is also triggered from the supply of connecting flights. As more non-stop routes have opened, consumers can fly a shorter flight where they do not have to wait in airports  during long layovers.

Data and Insights

Data is retrieved from Schiphol Statistics and it contains information on passengers and flights going through Schiphol every month since 1992 until July 2017. Passengers travelling within Europe have the largest share and also the highest volatility.

The data on transit passengers and those who travel outside of Europe used to follow the same trend until 1995. The divergence from this point corresponds with the time when Departure 3 was finalized, allowing for more international flights with a layover in Amsterdam and more transit passengers.

Summer holidays have the highest peaks and these peaks are repeated yearly. July and August are the preferred months to travel, while January and February are the least preferred ones. With respect to world-wide travelers, May scores a higher number of passengers than June and it might be due to a high number of bank holidays during this month, which travelers like to combine it with their holiday leave.

Figure 1: Passengers travelling through Schiphol every month since January 1992


In the Figure 2 below, we notice that the number of flights arriving and leaving to worldwide destinations has not increased at a comparable rate to that of the passengers leaving to world-wide destinations (Figure 1). Remarkably, its trend is also relatively flatter with smaller peaks during holiday season.

Compared to February 2017 , in July there was a 29% increase in the number of worldwide flights and a 44% increase in the number of passengers.

Compared to February 2017 , in July there was a 43% increase in the number of European flights and a 60% increase in the number of passengers.

Figure 2: Flights leaving and arriving in Schiphol every month since January 1992


This data shows that the number of passengers per intra-European flight is much more volatile than the number of passengers per worldwide flight. In Figure 3 we see that number of passengers per worldwide flight is reaching a steady state with very little variability amongst seasons.

Demand for such long flights ought to be much better calculated as the cost of having a free seat is higher for worldwide connections. Due to longer distances, higher travel prices condition movements of demand for long flights and make it easy to calculate passengers per flight.

Figure 3: Average number of passengers per flight in Schiphol every month since January 1992


The number of air passengers has increased at an increasing rate during the past thirty years. Competition, increase in technology and oil prices have pushed the fare prices down, making flying affordable to more people.

Airlines are buying more jets and increasing capacity per plane in order to meet the increasing demand. Summer holidays remain the favorite time for passengers to travel while the difference between low peak and high peak travelling is more visible in intra-European flights.

Download the full report: Is Compulsive Flying Disorder a Thing?

Extreme Weather Isn’t Small Potatoes for Agricultural Companies

Western Europe has seen an unusual heat wave during the past month due to hot air coming up from North Africa. Extreme-weather events frequently drive agricultural production fluctuations, increase price volatility, and create uncertainty on agricultural commodity markets. We can quantify this impact using the share prices of agricultural firms in the Netherlands, the world’s second largest agricultural exporter valued at nearly €92bn last year, behind only the US. Our data shows serious concerns about food production due to the heatwave and drought. Put simply, smaller potatoes are not small potatoes for share prices of major agricultural players.  

 The unusually warm and dry summer so far has provoked forest fires in Europe from Greece in the South to the Arctic Circle in Northern Sweden. According to the United Nations Regional Information Centre for Western Europe, 85% of the area burned in forest fires in Europe is in major agriculture exporting countries in Southern Europe, like Croatia, France, Greece, Italy, Portugal and Spain (UNRIC, 2018).

An article funded by European Commission Research Centre on Sustainable Resources, Chatzopoulos et al. (2017) posits that weather events affect commodity markets through a two-fold impact on crop production. The direct effect is biophysical and pertains to yield reduction when crops are hit by extreme weather at critical developmental stages. The indirect effect boils down to altering the efficiency and perhaps the timing of input application. This two-fold impact dictates fluctuations in production and stock-to-use ratios as well as price volatility at least in the short run.

A crop shortfall is a relevant short-term consequence with corresponding long-term implications for both area (planted or harvested) and intensity (number of crops grown within a period of time).

While simulation models of regional agriculture typically assume normal weather in deterministic scenarios, the current heatwave has thrown out production forecasts.  This has had a strong downside impact on agricultural firms.

At its most basic level, if investors observe that supply in commodities market is limited and profits are impacted, they foresee a fall in the earnings potential of the stock, which in turn reduces demand for the stock, resulting in lower prices.

If we define extreme weather by extreme temperatures, then days with average temperature below -2˚Celcius and above 23˚Celcius are considered extreme in the Netherlands. Since end of May 2016 until today, there are 52 extreme days registered in the Netherlands. The following table gives information about the average share price of three agricultural corporations – For Farmers NV, Wessanen NV and Amsterdam Commodities NV in normal days and extreme days since the end of May 2016.

Table 1: Average share prices of the three corporations: For Farmers NV and Amsterdam Commodity NV and Wessanen NV in normal and extreme weather

  Average Share Price
Extreme Weather 15.21
Normal Weather 15.45

As it can be noticed in the table above, the average share price for both of these corporations is slightly lower in days where weather is considered to be extreme. This effect can be observed in Figure 1 below where the share prices of both of the agricultural corporations started to go down once the average temperature started to exceed 23˚C in Mid-July 2018.

This effect is especially visible in the extremely warm days of the second last week of July, when temperatures hit a high of 28˚Celsius and the average share price of the basket hit the second low in 3 months of 14.17, to be followed with the yearly lowest on the 2nd of August of 14.02. Even though average temperatures are starting to get normalized, the confidence in earnings potential will take a bit longer to mature.

Figure 1: Stock prices of the basket average (For Farmers NV, Amsterdam Commodities NV, Wessanen NV) and average daily temperature in Amsterdam. 

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The claim above is not only true for the upper extreme temperatures. When compared to the average daily share price of the two commodities above since end of May 2016 which is 15.45 the average share price in extremely cold days is 15.25. Frozen ground and colder temperatures can affect planting, which has a direct impact on the commodity production and subsequently on investors’ confidence about performance in the agricultural sector.

This report looked at the possible impact that extreme weather has on share prices of a basket of agricultural corporations in the Netherlands. The link between the two can be approached through the lens of current and future low crop production which in turn affects corporations profit and sales. It becomes clear that July’s high temperatures and the lower share prices raise concerns about agricultural production in the Netherlands.

Download the full report: Extreme Weather Isn’t Small Potatoes for Agricultural Companies

The Forgotten Driver of the Dutch Housing Price Boom

The Dutch housing market is under pressure. Housing prices have experienced a continuous increase since an ever-low point after the financial crisis. Amsterdam noticed the highest increase in house prices among the big cities, but other cities also faced a significant growth. The reasons for this surge are numerous. At first, with a decrease in the supply of new houses, the overall supply of houses has decreased. On the demand side, low mortgage rates have made buying a house attractive as most buyers profit from overbidding once and paying low mortgage repayment for the rest of their loan. This excess demand has pushed overbidding to an all-time high, especially in urban areas like the big cities in Randstad. House price increases are detrimental on consumption capability and on urban housing affordability. As houses become more expensive, fewer people will be affording the high prices. 

Variables that affect housing prices are not usually as volatile as prices. However, the supply and demand forces have an immediate effect on the price. For example, supply shortages that are much bigger in big cities move at an opposite trend to increases in house prices. Keeping demand constant, shortage in the supply gives sellers a higher bargaining power on their asking price. Looking at this data more frequently is not only helpful to observe the evolution of houses sold or prices per house/square meter but also to analyze a potential relationship between supply and asking price. 

The following table gives details on the asking price per average house in The Netherlands in May 2018 and its percentage change as compared to April 2018:

Median Asking Price 

€ 286.948 


Average Asking Price 

€ 375.793 


Average Asking Price/square meter

€ 2.501 


As shown in Figure 1 below, the number of houses sold per month has decreased in all big four cities after the financial crisis. After it hit a decade-high by the end of 2012 and beginning of 2013, the number of houses sold today has experienced a decrease of 70% (Utrecht) to 96% (Amsterdam). If we assume that demand keeps at the same levels, a more suitable supply of housing is needed to overcome the problem of price increase.

Figure 1

Untitled drawing (1)

If we look at Figure 2, when compared to January 2013 when houses sold were at its highest record, prices per square meter have increased with 55% in Amsterdam, 31% in The Hague, 29% in Utrecht and 36% in Rotterdam. When compared to January 2013 when houses sold were at its highest record, average prices per house have increased with 65% in Amsterdam, 48% in The Hague, 38% in Utrecht and 57% in Rotterdam.

Figure 2


As interest rates are attractively higher, demand to live in metropolitan areas has been increasing and house prices have surged. Additionally, there is a shortage in new houses being built and it is granting home-owners greater bargaining power on their pricing strategy. In the case of the real-estate market, when the demand is high, supply has become a dominant driver on prices in The Netherlands.


Download the full report: The Forgotten Driver of the Dutch House Price Boom

The Impact of Ride-Sharing Platforms on Driver Wages in The Netherlands

During the past decade, ride-sharing (e-hailing) platforms like Uber, Ola, Grab, Lyft etc. have become very popular. The reasons behind this popularity lie on a variety of reasons: passengers value the convenience, safety and the fact that these platforms are considered cost-saving substitutes of taxi service. While in the U.S., the number of drivers joining e-hailing force has increased exponentially, in Europe taxi-drivers have rebelled following the launch of the service. The competition that the taxi drivers now face in the point-to-point transportation service industry is higher along with lower earnings potential.

For instance, as the demand for Uber increases, the earnings potential for self-employed drivers increases. For anyone to become a ride-sharing driver, all one needs is the relevant license, car registration and the app registered on their smart phone.

Ultimately, e-hailing platforms have incentivized not only taxi drivers but also non-taxi drivers to become self-employed drivers. E-hailing drivers enjoy the work flexibility the platform permits, while exhibiting higher hourly earnings than traditional taxi drivers. A possible explanation for these higher earnings of e-hailing drivers could be that these drivers benefit from higher capacity utilization as now they can find their passengers easily through the app and drive more rides per hour.

However, not all types of drivers utilize the app the same way. For that reason, the types of self-employed drivers are divided in three categories: start, medium and high. As a variety of micro, labour or macro variables have an effect on wages and wage fragmentation amongst industries, the task of finding the extent of capacity utilization becomes more difficult.

What happened to the wages and their increase of an average freelancer before and after the introduction of e-hailing platforms?

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Wages of all types of freelancers saw a sharp increase right after the financial crisis. During the financial crisis, due to increasing cost restrictions and a decrease in the demand, many business owners gave their employees advice to start for themselves and switch from wage-employed to self-employed contracts.

With work still to be done, business owners hired their former employees as freelancers. In turn, this move added a lot of new freelancers who had a lot of experience and therefore were able to collect higher wages. This could explain why the percentage change in the hourly wages of the high type was higher than when compared to the rest.

Collection bias may also be in play as respondents to the Rate guide shifted from starters to more experienced workers and as a result the difference between high and low types increased further. After e-hailing was introduced there is little volatility afterward for all three types of jobs.

Did the hourly wages of self-employed drivers increase after the introduction of e-hailing platforms?

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In Figure 2 (below) we can see the trend of hourly wages of the three categories of drivers (start, medium and high). As it can be observed, there is a slight increase in the hourly wages short after e-hailing introduction. In fact, drivers in the start function earned on average 17.18 euros per hour before and 21.21 euros after the introduction of e-hailing (an increase of 23.4%). Medium drivers earned on average 20.63 euros per hour and after 24.73 euros per hour (an increase of 18.86%). High driver used to earn on average 24 euros per hour before e-hailing and now they earn on average 26.68 euros per hour, or an increase of 11.16% more.


Consumers perceive ride-sharing platforms as cost-saving substitutes of taxis. Therefore, the preferred service is the one with the lowest price and the ones who get a bigger share of the market will be the start-type drivers. After e-hailing implementation, all types of drivers can make use of the platform to find costumers more easily and save on gas by driving around to find them. However, demand is quite sensible to prices as costumers consider e-hailing as a cost-saving platform. A complementary explanation to why the starting type saw a higher increase is the flexibility terms that e-hailing platforms have in the work supplied. Drivers can choose their own driving time and places to operate. This incentivized non-drivers to become self-employed drivers of the starting type, which increased the hourly wages of the start-type.

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Is there a significant difference between drivers wage increase and other professions wage increase?

After the introduction of ride-sharing platforms, drivers of all categories saw a much smaller increase in their wages than an average freelancer. This could hint that competition kept the wage growth at a minimum for drivers. Within the average freelancers group, the hourly wage of a freelancer of high type increased more than the hourly wages of an average freelancer of start or medium type. For a self-employed driver the opposite happened: The hourly wage of the start type drivers increased more than other categories.

Using alternative data on freelancer’s wages, this report aimed to answer whether ride-sharing platforms have had a positive impact on drivers wages in the Netherlands. When compared to the wages of average freelancers of any type (start, medium and high), the wages of freelance drivers increased much less.

All told, hard data suggests drive hailing apps are not the absolute antagonists portrayed in media both traditional and social. Yet stagnating wage growth compared to the rest of the economy shows that new business models disrupt not only the user experience and the gig economy, but society as a whole.

What limits our findings?

First, wages used in this work are derived from a mathematical calculation per each type of work of any profession. Given a level of education, experience and a set of factors that affect wages, Bosman (2018) is able to determine the market value of any freelancer. These data might not always correspond with the real wages.

Second, changes in wages before and after ride-sharing came to Holland could have been affected by a number of variables that might or might not be related to Uber. After all in order to prove a shock impact of Uber on drivers’ wages, one needs a set of variables that affect wages and data that is more frequently measured. In order to prove causation, a proper econometric model would have been used, had we included in our analysis a full set of time-varying characteristics including the unemployment rate, the share of the population with a college degree, the female population share, and age groups etc.

Last, as Bosman (2018) already controls for heterogeneity factors between drivers and freelancers in types of work, the problem of between-heterogeneity is solved to a certain degree but not to the fullest as factors might not capture all heterogeneity issues in between.

Download the full report: The Impact of Ride-Sharing Platforms on Driver Wages in The Netherlands